Vibecode Pipedrive
track this build5 phases, 15 steps, beginner friendly0%KINDA · weekend project
The core loop is buildable, but a dependable replacement becomes a real weekend or multi-day project. For Pipedrive, manage contacts and deals through a visual pipeline with activities and reminders. The hard boundary is email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish, plus integrations, data quality, and workflow lock-in.
the project pack5 files · written for this build, step by step
You are building a lean indie version of Pipedrive. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Pipedrive · indie build Build a deal pipeline with dated activity and honest value summaries. Estimated effort: **multi-day**. Work `BUILD_PLAN.md` top to bottom · every phase ends in a check that has to pass before the next one starts. ## Stack | Part | Choice | Why | | --- | --- | --- | | Runtime | Python 3.12+ and Flask | A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. | | Storage | SQLite through Python sqlite3 | Local ownership with explicit transactions and a portable backup path. | | Interface | Jinja HTML templates, CSS and vanilla JavaScript | Implement the specified screens directly with labelled controls and progressive enhancement. | | Verification | Python unittest and browser acceptance fixtures | Check invariants and the actual user workflow before the next phase. | ## Before you start Have every one of these ready. The plan assumes them from step one. - [ ] **Python 3.12 or newer and a terminal** · Python is free; this local prototype requires no hosting subscription. - Why: The local backend, tests and storage use Python. - Get it: Install Python from python.org. Open a terminal in a new empty project folder. On Windows, use py -3 where this guide says python if python is not on PATH; on macOS/Linux use python3 if needed. Create .venv and activate it before installing packages. - Verify: python --version reports 3.12+ and python -c "import sqlite3" succeeds. - [ ] **A current desktop browser and text editor** · No paid service required for this local step. - Why: You need to view the local interface and edit generated project files. - Get it: Use an installed Chrome, Firefox or Edge browser. Open the empty project folder in your editor; open the terminal there, not in this catalog repository. - Verify: You can create a text file in the project folder and open browser developer tools. - [ ] **Pipedrive acceptance sample** · No paid service required for this local step. - Why: This fixture makes the first end-to-end check reproducible. - Get it: Create synthetic sample data before implementation: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Save it under fixtures/ with the expected results in fixtures/README.md; use no real credentials or customer records. - Verify: The fixture files and expected outcomes exist and can be inspected without a vendor account. - [ ] **Confirm the bounded replacement** · No paid service required for this local step. - Why: The full commercial product is larger than this guide. - Get it: The deliverable is a deal pipeline with dated activity and honest value summaries. Read every exclusion below. Indie mode runs locally; any public or shared use requires the product access and deployment gates first. - Verify: You can name the primary workflow and the vendor features this version deliberately leaves out. ## Quick start ```sh python -m venv .venv python -m pip install Flask Flask-WTF python-dotenv waitress tzdata python -m pip freeze > requirements.txt python -m flask --app app run --host 127.0.0.1 ``` Then copy `.env.example` to `.env` and fill in the values it documents. ## Honest limits This build deliberately does not replace: - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish - automatic email and calendar capture - data enrichment - large integration ecosystem - enterprise reporting If one of those is essential to you, that is the reason to keep paying for Pipedrive, and the README should say so rather than pretend. ===== BRIEF.md ===== # Build brief · Pipedrive The one-shot brief this plan expands. `BUILD_PLAN.md` (or `MILESTONES.md`) is the same sequence broken into steps and checks; where the two disagree, the plan wins. Build me a deal pipeline with dated activity and honest value summaries as a bounded replacement for Pipedrive. Build it in phases in the order below. Do not write the whole product in one pass. Finish the current phase, run its Done when checks, fix failures, then continue. Indie mode completes Phases 1-5. Phase 6 is required before shared or public deployment. ### Stack (fixed, do not substitute) - Runtime: Python 3.12+ and Flask. A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. - Storage: SQLite through Python sqlite3. Local ownership with explicit transactions and a portable backup path. - Interface: Jinja HTML templates, CSS and vanilla JavaScript. Implement the specified screens directly with labelled controls and progressive enhancement. - Verification: Python unittest and browser acceptance fixtures. Check invariants and the actual user workflow before the next phase. ### Data model (create this before Phase 1) - contacts(id,name,email) - stages(id,name,position) - deals(id,contact_id,title,amount_minor,currency,stage_id,state) - activities(id,deal_id,due_at,type,done) - stage_events(id,deal_id,from_stage,to_stage,at) - Use stable ids and explicit relationships; add auxiliary tables named by the phases before those phases use them. - Acceptance fixture: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. ### Prerequisites and configuration - Python 3.12 or newer and a terminal: Install Python from python.org. Open a terminal in a new empty project folder. On Windows, use py -3 where this guide says python if python is not on PATH; on macOS/Linux use python3 if needed. Create .venv and activate it before installing packages. Verify: python --version reports 3.12+ and python -c "import sqlite3" succeeds. Cost: Python is free; this local prototype requires no hosting subscription. - A current desktop browser and text editor: Use an installed Chrome, Firefox or Edge browser. Open the empty project folder in your editor; open the terminal there, not in this catalog repository. Verify: You can create a text file in the project folder and open browser developer tools. Cost: No paid service required for this local step. - Pipedrive acceptance sample: Create synthetic sample data before implementation: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Save it under fixtures/ with the expected results in fixtures/README.md; use no real credentials or customer records. Verify: The fixture files and expected outcomes exist and can be inspected without a vendor account. Cost: No paid service required for this local step. - Confirm the bounded replacement: The deliverable is a deal pipeline with dated activity and honest value summaries. Read every exclusion below. Indie mode runs locally; any public or shared use requires the product access and deployment gates first. Verify: You can name the primary workflow and the vendor features this version deliberately leaves out. Cost: No paid service required for this local step. - Configuration: DATA_DIR, SECRET_KEY, APP_MODE, SITE_URL. Ship .env.example, replace placeholders and exclude secrets from git. ### Phase 1 · Local foundation and data contract Build: Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. - Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Commands, after creating the named files: `python -m venv .venv`; `python -m pip install Flask Flask-WTF python-dotenv waitress tzdata`; `python -m pip freeze > requirements.txt`; `python -m flask --app app run --host 127.0.0.1`. - For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Commands, after creating the named files: `python manage.py init`; `python manage.py seed`. - Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. - Trap: The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. Done when: The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. Restarting preserves the seeded records or canonical files; running init again deletes nothing. A cross-origin state-changing request to an admin route is refused. Do not build yet: Do not start deals and stages until these checks pass. ### Phase 2 · Deals and stages Build: Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Move deals between stages in a transaction and append stage history; support won/lost states separately. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Money stored as floating point creates avoidable rounding errors. Done when: Moving a deal produces one dated event and preserves its amount. A negative deal amount fails validation. Do not build yet: Do not start next activities until these checks pass. ### Phase 3 · Next activities Build: Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. - Add call, meeting and follow-up activities with due time and completion history. - Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Recording a planned call is not proof that a call happened. Done when: Completing the last activity puts the still-open deal in no-next-action. A won deal is excluded from the open follow-up inbox. Do not build yet: Do not start pipeline reporting until these checks pass. ### Phase 4 · Pipeline reporting Build: Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Import/export deals and activities with stable ids and a merge preview for existing contacts. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Forecast probabilities must be user-defined and labelled estimates, not predictions. Done when: The fixture reports USD 350 and a separate EUR total, never a combined number. Reimporting the same exported deal ids does not duplicate revenue. Do not build yet: Do not start portable delivery and clean-start proof until these checks pass. ### Phase 5 · Portable delivery and clean-start proof Build: Finish the Pipedrive replacement with a documented first-run path and a recoverable export. - Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. - Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. - Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Commands, after creating the named files: `python -m pip install -r requirements.txt`; `python -m unittest discover -s test`. - Trap: Export without an import or restore rehearsal is not verified portability. Done when: A new folder reaches the documented fixture outcome using only README instructions. A backup restored in isolation preserves the proof data and can be opened. Do not build yet: Do not start operate and share with access controls until these checks pass. ### Phase 6 · Operate and share with access controls (product-builder only) Build: Product-builder only: make a deal pipeline with dated activity and honest value summaries operable for its stated audience before allowing remote access. - Add owner/member/viewer authorization as appropriate, password hashes through Werkzeug, expiring server-side sessions, CSRF and login rate limits. Add users, sessions and audit schema migrations plus an owner-init command prompting securely for its password. Enforce ownership on every private read/write/download and fail closed when product setup is incomplete. Existing learner or admin identities must use this same boundary. - Serve app:app with Waitress on loopback behind Caddy HTTPS. Configure trusted proxy headers narrowly, Secure/HttpOnly/SameSite cookies, upload limits, request ids and structured logs without private content. Run background jobs as a separate supervised process when the domain workflow requires them. Commands, after creating the named files: `waitress-serve --listen=127.0.0.1:5000 app:app`. - Add a scheduled encrypted off-host backup using this procedure: Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Monitor health, disk space, failed jobs and backup age. Stop the service to test an alert; rehearse recovery with outbound effects disabled and record recovery time. Rotate any exposed credentials and require reconciliation before resuming queues. - Trap: Product mode is additional engineering, not a switch that makes a local prototype production-ready. Done when: An unauthenticated visitor cannot read private records, download private files or mutate the admin surface. A viewer cannot mutate data by making a direct request, and guessed ids cannot cross ownership boundaries. Stopping the service triggers the configured alert and the latest off-host backup restores the fixture in isolation. Do not build yet: Do not add new providers or vendor-scale features until the release gates are recorded. ### Out of scope (and why) - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish: retain the paid product if this capability is essential; it is outside this bounded build. - automatic email and calendar capture: retain the paid product if this capability is essential; it is outside this bounded build. - data enrichment: retain the paid product if this capability is essential; it is outside this bounded build. - large integration ecosystem: retain the paid product if this capability is essential; it is outside this bounded build. - enterprise reporting: retain the paid product if this capability is essential; it is outside this bounded build. ### README must contain - Exact install, configure, initialize, start, test and recovery commands for a clean folder. - The schema, fixture, acceptance results, private data locations and export format. - Every prerequisite and secret source, actual running costs and deliberately excluded capabilities. - An honest distinction between tests actually run and checks still awaiting real credentials or deployment. - Dependency documentation reviewed 2026-09-05: https://flask.palletsprojects.com/en/stable/installation/ ; https://docs.python.org/3/library/sqlite3.html ; https://flask-wtf.readthedocs.io/en/1.2.x/csrf/ ; https://docs.pylonsproject.org/projects/waitress/en/stable/usage.html. Recheck before upgrading; freeze the versions actually tested. ===== AGENTS.md ===== # Agent instructions · Pipedrive indie build - Read `README.md` and `BUILD_PLAN.md` before writing code. The stack is fixed: Python 3.12+ and Flask, SQLite through Python sqlite3, Jinja HTML templates, CSS and vanilla JavaScript, Python unittest and browser acceptance fixtures. Do not substitute. - Work one phase at a time, in order. Do not start a phase until every "Done when" item of the previous one passes. - Prefer the fewest moving parts that satisfy the step. No frameworks, services or dependencies the plan does not name. - Secrets live in `.env`, never in source or logs. Keep `.env.example` current when a variable is introduced. - Do not invent cryptography, security guarantees, APIs or compliance claims. - Add a focused test for every destructive, security-sensitive or data-loss path the plan names. - Run the project checks before declaring a phase complete, and record any deliberate shortcut in the README under "Tradeoffs". ## Known traps - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. - Money stored as floating point creates avoidable rounding errors. - Recording a planned call is not proof that a call happened. - Forecast probabilities must be user-defined and labelled estimates, not predictions. - Export without an import or restore rehearsal is not verified portability. ===== BUILD_PLAN.md ===== # Build plan · Pipedrive Build a deal pipeline with dated activity and honest value summaries. Phases are in dependency order. Each ends in a "Done when" list; treat an unticked item as a blocker, not a note. ## Phase 1 · Local foundation and data contract Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. ### Steps 1. Create and start the local application Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Files: `app.py`, `requirements.txt`, `.env.example`, `.gitignore` ```sh python -m venv .venv python -m pip install Flask Flask-WTF python-dotenv waitress tzdata python -m pip freeze > requirements.txt python -m flask --app app run --host 127.0.0.1 ``` 2. Implement storage and seed the named fixture For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Files: `schema.sql`, `db.py`, `manage.py`, `fixtures/README.md` ```sh python manage.py init python manage.py seed ``` 3. Protect the local request boundary Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. Files: `app.py`, `templates/base.html`, `test/test_foundation.py` ### Done when - [ ] The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. - [ ] Restarting preserves the seeded records or canonical files; running init again deletes nothing. - [ ] A cross-origin state-changing request to an admin route is refused. ### Watch out - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. ## Phase 2 · Deals and stages Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. ### Steps 1. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Files: `features/deals_and_stages.py`, `templates/deals_and_stages.html` 2. Move deals between stages in a transaction and append stage history; support won/lost states separately. Move deals between stages in a transaction and append stage history; support won/lost states separately. Files: `features/deals_and_stages.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_deals_and_stages.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Moving a deal produces one dated event and preserves its amount. - [ ] A negative deal amount fails validation. ### Watch out - Money stored as floating point creates avoidable rounding errors. ## Phase 3 · Next activities Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. ### Steps 1. Add call, meeting and follow-up activities with due time and completion history. Add call, meeting and follow-up activities with due time and completion history. Files: `features/next_activities.py`, `templates/next_activities.html` 2. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Files: `features/next_activities.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_next_activities.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Completing the last activity puts the still-open deal in no-next-action. - [ ] A won deal is excluded from the open follow-up inbox. ### Watch out - Recording a planned call is not proof that a call happened. ## Phase 4 · Pipeline reporting Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. ### Steps 1. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Files: `features/pipeline_reporting.py`, `templates/pipeline_reporting.html` 2. Import/export deals and activities with stable ids and a merge preview for existing contacts. Import/export deals and activities with stable ids and a merge preview for existing contacts. Files: `features/pipeline_reporting.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_pipeline_reporting.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] The fixture reports USD 350 and a separate EUR total, never a combined number. - [ ] Reimporting the same exported deal ids does not duplicate revenue. ### Watch out - Forecast probabilities must be user-defined and labelled estimates, not predictions. ## Phase 5 · Portable delivery and clean-start proof Finish the Pipedrive replacement with a documented first-run path and a recoverable export. ### Steps 1. Write the user-facing runbook Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. Files: `README.md`, `.env.example` 2. Create and rehearse a recoverable backup Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. Files: `OPERATIONS.md`, `scripts/backup.py` 3. Reproduce the first-run experience Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Files: `README.md`, `verification.md` ```sh python -m pip install -r requirements.txt python -m unittest discover -s test ``` ### Done when - [ ] A new folder reaches the documented fixture outcome using only README instructions. - [ ] A backup restored in isolation preserves the proof data and can be opened. ### Watch out - Export without an import or restore rehearsal is not verified portability. ## Not in this build - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish - automatic email and calendar capture - data enrichment - large integration ecosystem - enterprise reporting ## After v1, if you want it - Extend pipeline reporting only after the fixture and recovery checks pass. - Before adding another integration, document its credentials, limits, cost and failure behavior with primary-source links. ===== .env.example ===== # Copy to .env and fill in. Never commit .env; this file documents it. # Required. A new private folder this application creates on first run; never serve it as static files. DATA_DIR=./data/pipedrive # Required · secret. Generate with python -c "import secrets; print(secrets.token_hex(32))" and save only in .env. SECRET_KEY=replace-with-a-random-secret # Required. Use indie for loopback-only personal work. Product mode must refuse to start until owner login and the deployment gates are configured. APP_MODE=indie # Required. The origin used for local forms and links; replace with the chosen HTTPS origin in product mode. SITE_URL=http://127.0.0.1:5000
You are building a lean indie version of Pipedrive. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Pipedrive · indie build Build a deal pipeline with dated activity and honest value summaries. Estimated effort: **multi-day**. Work `BUILD_PLAN.md` top to bottom · every phase ends in a check that has to pass before the next one starts. ## Stack | Part | Choice | Why | | --- | --- | --- | | Runtime | Python 3.12+ and Flask | A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. | | Storage | SQLite through Python sqlite3 | Local ownership with explicit transactions and a portable backup path. | | Interface | Jinja HTML templates, CSS and vanilla JavaScript | Implement the specified screens directly with labelled controls and progressive enhancement. | | Verification | Python unittest and browser acceptance fixtures | Check invariants and the actual user workflow before the next phase. | ## Before you start Have every one of these ready. The plan assumes them from step one. - [ ] **Python 3.12 or newer and a terminal** · Python is free; this local prototype requires no hosting subscription. - Why: The local backend, tests and storage use Python. - Get it: Install Python from python.org. Open a terminal in a new empty project folder. On Windows, use py -3 where this guide says python if python is not on PATH; on macOS/Linux use python3 if needed. Create .venv and activate it before installing packages. - Verify: python --version reports 3.12+ and python -c "import sqlite3" succeeds. - [ ] **A current desktop browser and text editor** · No paid service required for this local step. - Why: You need to view the local interface and edit generated project files. - Get it: Use an installed Chrome, Firefox or Edge browser. Open the empty project folder in your editor; open the terminal there, not in this catalog repository. - Verify: You can create a text file in the project folder and open browser developer tools. - [ ] **Pipedrive acceptance sample** · No paid service required for this local step. - Why: This fixture makes the first end-to-end check reproducible. - Get it: Create synthetic sample data before implementation: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Save it under fixtures/ with the expected results in fixtures/README.md; use no real credentials or customer records. - Verify: The fixture files and expected outcomes exist and can be inspected without a vendor account. - [ ] **Confirm the bounded replacement** · No paid service required for this local step. - Why: The full commercial product is larger than this guide. - Get it: The deliverable is a deal pipeline with dated activity and honest value summaries. Read every exclusion below. Indie mode runs locally; any public or shared use requires the product access and deployment gates first. - Verify: You can name the primary workflow and the vendor features this version deliberately leaves out. ## Quick start ```sh python -m venv .venv python -m pip install Flask Flask-WTF python-dotenv waitress tzdata python -m pip freeze > requirements.txt python -m flask --app app run --host 127.0.0.1 ``` Then copy `.env.example` to `.env` and fill in the values it documents. ## Honest limits This build deliberately does not replace: - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish - automatic email and calendar capture - data enrichment - large integration ecosystem - enterprise reporting If one of those is essential to you, that is the reason to keep paying for Pipedrive, and the README should say so rather than pretend. ===== BRIEF.md ===== # Build brief · Pipedrive The one-shot brief this plan expands. `BUILD_PLAN.md` (or `MILESTONES.md`) is the same sequence broken into steps and checks; where the two disagree, the plan wins. Build me a deal pipeline with dated activity and honest value summaries as a bounded replacement for Pipedrive. Build it in phases in the order below. Do not write the whole product in one pass. Finish the current phase, run its Done when checks, fix failures, then continue. Indie mode completes Phases 1-5. Phase 6 is required before shared or public deployment. ### Stack (fixed, do not substitute) - Runtime: Python 3.12+ and Flask. A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. - Storage: SQLite through Python sqlite3. Local ownership with explicit transactions and a portable backup path. - Interface: Jinja HTML templates, CSS and vanilla JavaScript. Implement the specified screens directly with labelled controls and progressive enhancement. - Verification: Python unittest and browser acceptance fixtures. Check invariants and the actual user workflow before the next phase. ### Data model (create this before Phase 1) - contacts(id,name,email) - stages(id,name,position) - deals(id,contact_id,title,amount_minor,currency,stage_id,state) - activities(id,deal_id,due_at,type,done) - stage_events(id,deal_id,from_stage,to_stage,at) - Use stable ids and explicit relationships; add auxiliary tables named by the phases before those phases use them. - Acceptance fixture: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. ### Prerequisites and configuration - Python 3.12 or newer and a terminal: Install Python from python.org. Open a terminal in a new empty project folder. On Windows, use py -3 where this guide says python if python is not on PATH; on macOS/Linux use python3 if needed. Create .venv and activate it before installing packages. Verify: python --version reports 3.12+ and python -c "import sqlite3" succeeds. Cost: Python is free; this local prototype requires no hosting subscription. - A current desktop browser and text editor: Use an installed Chrome, Firefox or Edge browser. Open the empty project folder in your editor; open the terminal there, not in this catalog repository. Verify: You can create a text file in the project folder and open browser developer tools. Cost: No paid service required for this local step. - Pipedrive acceptance sample: Create synthetic sample data before implementation: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Save it under fixtures/ with the expected results in fixtures/README.md; use no real credentials or customer records. Verify: The fixture files and expected outcomes exist and can be inspected without a vendor account. Cost: No paid service required for this local step. - Confirm the bounded replacement: The deliverable is a deal pipeline with dated activity and honest value summaries. Read every exclusion below. Indie mode runs locally; any public or shared use requires the product access and deployment gates first. Verify: You can name the primary workflow and the vendor features this version deliberately leaves out. Cost: No paid service required for this local step. - Configuration: DATA_DIR, SECRET_KEY, APP_MODE, SITE_URL. Ship .env.example, replace placeholders and exclude secrets from git. ### Phase 1 · Local foundation and data contract Build: Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. - Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Commands, after creating the named files: `python -m venv .venv`; `python -m pip install Flask Flask-WTF python-dotenv waitress tzdata`; `python -m pip freeze > requirements.txt`; `python -m flask --app app run --host 127.0.0.1`. - For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Commands, after creating the named files: `python manage.py init`; `python manage.py seed`. - Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. - Trap: The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. Done when: The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. Restarting preserves the seeded records or canonical files; running init again deletes nothing. A cross-origin state-changing request to an admin route is refused. Do not build yet: Do not start deals and stages until these checks pass. ### Phase 2 · Deals and stages Build: Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Move deals between stages in a transaction and append stage history; support won/lost states separately. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Money stored as floating point creates avoidable rounding errors. Done when: Moving a deal produces one dated event and preserves its amount. A negative deal amount fails validation. Do not build yet: Do not start next activities until these checks pass. ### Phase 3 · Next activities Build: Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. - Add call, meeting and follow-up activities with due time and completion history. - Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Recording a planned call is not proof that a call happened. Done when: Completing the last activity puts the still-open deal in no-next-action. A won deal is excluded from the open follow-up inbox. Do not build yet: Do not start pipeline reporting until these checks pass. ### Phase 4 · Pipeline reporting Build: Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Import/export deals and activities with stable ids and a merge preview for existing contacts. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Forecast probabilities must be user-defined and labelled estimates, not predictions. Done when: The fixture reports USD 350 and a separate EUR total, never a combined number. Reimporting the same exported deal ids does not duplicate revenue. Do not build yet: Do not start portable delivery and clean-start proof until these checks pass. ### Phase 5 · Portable delivery and clean-start proof Build: Finish the Pipedrive replacement with a documented first-run path and a recoverable export. - Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. - Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. - Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Commands, after creating the named files: `python -m pip install -r requirements.txt`; `python -m unittest discover -s test`. - Trap: Export without an import or restore rehearsal is not verified portability. Done when: A new folder reaches the documented fixture outcome using only README instructions. A backup restored in isolation preserves the proof data and can be opened. Do not build yet: Do not start operate and share with access controls until these checks pass. ### Phase 6 · Operate and share with access controls (product-builder only) Build: Product-builder only: make a deal pipeline with dated activity and honest value summaries operable for its stated audience before allowing remote access. - Add owner/member/viewer authorization as appropriate, password hashes through Werkzeug, expiring server-side sessions, CSRF and login rate limits. Add users, sessions and audit schema migrations plus an owner-init command prompting securely for its password. Enforce ownership on every private read/write/download and fail closed when product setup is incomplete. Existing learner or admin identities must use this same boundary. - Serve app:app with Waitress on loopback behind Caddy HTTPS. Configure trusted proxy headers narrowly, Secure/HttpOnly/SameSite cookies, upload limits, request ids and structured logs without private content. Run background jobs as a separate supervised process when the domain workflow requires them. Commands, after creating the named files: `waitress-serve --listen=127.0.0.1:5000 app:app`. - Add a scheduled encrypted off-host backup using this procedure: Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Monitor health, disk space, failed jobs and backup age. Stop the service to test an alert; rehearse recovery with outbound effects disabled and record recovery time. Rotate any exposed credentials and require reconciliation before resuming queues. - Trap: Product mode is additional engineering, not a switch that makes a local prototype production-ready. Done when: An unauthenticated visitor cannot read private records, download private files or mutate the admin surface. A viewer cannot mutate data by making a direct request, and guessed ids cannot cross ownership boundaries. Stopping the service triggers the configured alert and the latest off-host backup restores the fixture in isolation. Do not build yet: Do not add new providers or vendor-scale features until the release gates are recorded. ### Out of scope (and why) - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish: retain the paid product if this capability is essential; it is outside this bounded build. - automatic email and calendar capture: retain the paid product if this capability is essential; it is outside this bounded build. - data enrichment: retain the paid product if this capability is essential; it is outside this bounded build. - large integration ecosystem: retain the paid product if this capability is essential; it is outside this bounded build. - enterprise reporting: retain the paid product if this capability is essential; it is outside this bounded build. ### README must contain - Exact install, configure, initialize, start, test and recovery commands for a clean folder. - The schema, fixture, acceptance results, private data locations and export format. - Every prerequisite and secret source, actual running costs and deliberately excluded capabilities. - An honest distinction between tests actually run and checks still awaiting real credentials or deployment. - Dependency documentation reviewed 2026-09-05: https://flask.palletsprojects.com/en/stable/installation/ ; https://docs.python.org/3/library/sqlite3.html ; https://flask-wtf.readthedocs.io/en/1.2.x/csrf/ ; https://docs.pylonsproject.org/projects/waitress/en/stable/usage.html. Recheck before upgrading; freeze the versions actually tested. ===== AGENTS.md ===== # Agent instructions · Pipedrive indie build - Read `README.md` and `BUILD_PLAN.md` before writing code. The stack is fixed: Python 3.12+ and Flask, SQLite through Python sqlite3, Jinja HTML templates, CSS and vanilla JavaScript, Python unittest and browser acceptance fixtures. Do not substitute. - Work one phase at a time, in order. Do not start a phase until every "Done when" item of the previous one passes. - Prefer the fewest moving parts that satisfy the step. No frameworks, services or dependencies the plan does not name. - Secrets live in `.env`, never in source or logs. Keep `.env.example` current when a variable is introduced. - Do not invent cryptography, security guarantees, APIs or compliance claims. - Add a focused test for every destructive, security-sensitive or data-loss path the plan names. - Run the project checks before declaring a phase complete, and record any deliberate shortcut in the README under "Tradeoffs". ## Known traps - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. - Money stored as floating point creates avoidable rounding errors. - Recording a planned call is not proof that a call happened. - Forecast probabilities must be user-defined and labelled estimates, not predictions. - Export without an import or restore rehearsal is not verified portability. ===== BUILD_PLAN.md ===== # Build plan · Pipedrive Build a deal pipeline with dated activity and honest value summaries. Phases are in dependency order. Each ends in a "Done when" list; treat an unticked item as a blocker, not a note. ## Phase 1 · Local foundation and data contract Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. ### Steps 1. Create and start the local application Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Files: `app.py`, `requirements.txt`, `.env.example`, `.gitignore` ```sh python -m venv .venv python -m pip install Flask Flask-WTF python-dotenv waitress tzdata python -m pip freeze > requirements.txt python -m flask --app app run --host 127.0.0.1 ``` 2. Implement storage and seed the named fixture For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Files: `schema.sql`, `db.py`, `manage.py`, `fixtures/README.md` ```sh python manage.py init python manage.py seed ``` 3. Protect the local request boundary Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. Files: `app.py`, `templates/base.html`, `test/test_foundation.py` ### Done when - [ ] The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. - [ ] Restarting preserves the seeded records or canonical files; running init again deletes nothing. - [ ] A cross-origin state-changing request to an admin route is refused. ### Watch out - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. ## Phase 2 · Deals and stages Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. ### Steps 1. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Files: `features/deals_and_stages.py`, `templates/deals_and_stages.html` 2. Move deals between stages in a transaction and append stage history; support won/lost states separately. Move deals between stages in a transaction and append stage history; support won/lost states separately. Files: `features/deals_and_stages.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_deals_and_stages.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Moving a deal produces one dated event and preserves its amount. - [ ] A negative deal amount fails validation. ### Watch out - Money stored as floating point creates avoidable rounding errors. ## Phase 3 · Next activities Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. ### Steps 1. Add call, meeting and follow-up activities with due time and completion history. Add call, meeting and follow-up activities with due time and completion history. Files: `features/next_activities.py`, `templates/next_activities.html` 2. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Files: `features/next_activities.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_next_activities.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Completing the last activity puts the still-open deal in no-next-action. - [ ] A won deal is excluded from the open follow-up inbox. ### Watch out - Recording a planned call is not proof that a call happened. ## Phase 4 · Pipeline reporting Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. ### Steps 1. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Files: `features/pipeline_reporting.py`, `templates/pipeline_reporting.html` 2. Import/export deals and activities with stable ids and a merge preview for existing contacts. Import/export deals and activities with stable ids and a merge preview for existing contacts. Files: `features/pipeline_reporting.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_pipeline_reporting.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] The fixture reports USD 350 and a separate EUR total, never a combined number. - [ ] Reimporting the same exported deal ids does not duplicate revenue. ### Watch out - Forecast probabilities must be user-defined and labelled estimates, not predictions. ## Phase 5 · Portable delivery and clean-start proof Finish the Pipedrive replacement with a documented first-run path and a recoverable export. ### Steps 1. Write the user-facing runbook Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. Files: `README.md`, `.env.example` 2. Create and rehearse a recoverable backup Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. Files: `OPERATIONS.md`, `scripts/backup.py` 3. Reproduce the first-run experience Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Files: `README.md`, `verification.md` ```sh python -m pip install -r requirements.txt python -m unittest discover -s test ``` ### Done when - [ ] A new folder reaches the documented fixture outcome using only README instructions. - [ ] A backup restored in isolation preserves the proof data and can be opened. ### Watch out - Export without an import or restore rehearsal is not verified portability. ## Not in this build - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish - automatic email and calendar capture - data enrichment - large integration ecosystem - enterprise reporting ## After v1, if you want it - Extend pipeline reporting only after the fixture and recovery checks pass. - Before adding another integration, document its credentials, limits, cost and failure behavior with primary-source links. ===== .env.example ===== # Copy to .env and fill in. Never commit .env; this file documents it. # Required. A new private folder this application creates on first run; never serve it as static files. DATA_DIR=./data/pipedrive # Required · secret. Generate with python -c "import secrets; print(secrets.token_hex(32))" and save only in .env. SECRET_KEY=replace-with-a-random-secret # Required. Use indie for loopback-only personal work. Product mode must refuse to start until owner login and the deployment gates are configured. APP_MODE=indie # Required. The origin used for local forms and links; replace with the chosen HTTPS origin in product mode. SITE_URL=http://127.0.0.1:5000
You are building a production product version of Pipedrive. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== PRODUCT.md ===== # Pipedrive · product brief ## Problem The core loop is buildable, but a dependable replacement becomes a real weekend or multi-day project. For Pipedrive, manage contacts and deals through a visual pipeline with activities and reminders. The hard boundary is email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish, plus integrations, data quality, and workflow lock-in. ## Product outcome An operated version of a deal pipeline with dated activity and honest value summaries, with authorized access, restore evidence and honest scope limits. ## Target user A builder who needs a maintainable product foundation, not a one-off demo. ## Required capabilities - Docker - PostgreSQL - self-hosted server - optional email API credentials ## Explicit non-goals for v1 - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish - automatic email and calendar capture - data enrichment - large integration ecosystem - enterprise reporting ## Success criteria - Moving a deal produces one dated event and preserves its amount. - Completing the last activity puts the still-open deal in no-next-action. - The fixture reports USD 350 and a separate EUR total, never a combined number. - A private-data authorization check passes using a second identity. - An off-host restore drill has a date, observed result and recovery time in OPERATIONS.md. - README names the excluded vendor capabilities and actual provider/hosting costs. ===== BRIEF.md ===== # Build brief · Pipedrive The one-shot brief this plan expands. `BUILD_PLAN.md` (or `MILESTONES.md`) is the same sequence broken into steps and checks; where the two disagree, the plan wins. Build me a deal pipeline with dated activity and honest value summaries as a bounded replacement for Pipedrive. Build it in phases in the order below. Do not write the whole product in one pass. Finish the current phase, run its Done when checks, fix failures, then continue. Indie mode completes Phases 1-5. Phase 6 is required before shared or public deployment. ### Stack (fixed, do not substitute) - Runtime: Python 3.12+ and Flask. A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. - Storage: SQLite through Python sqlite3. Local ownership with explicit transactions and a portable backup path. - Interface: Jinja HTML templates, CSS and vanilla JavaScript. Implement the specified screens directly with labelled controls and progressive enhancement. - Verification: Python unittest and browser acceptance fixtures. Check invariants and the actual user workflow before the next phase. ### Data model (create this before Phase 1) - contacts(id,name,email) - stages(id,name,position) - deals(id,contact_id,title,amount_minor,currency,stage_id,state) - activities(id,deal_id,due_at,type,done) - stage_events(id,deal_id,from_stage,to_stage,at) - Use stable ids and explicit relationships; add auxiliary tables named by the phases before those phases use them. - Acceptance fixture: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. ### Prerequisites and configuration - Python 3.12 or newer and a terminal: Install Python from python.org. Open a terminal in a new empty project folder. On Windows, use py -3 where this guide says python if python is not on PATH; on macOS/Linux use python3 if needed. Create .venv and activate it before installing packages. Verify: python --version reports 3.12+ and python -c "import sqlite3" succeeds. Cost: Python is free; this local prototype requires no hosting subscription. - A current desktop browser and text editor: Use an installed Chrome, Firefox or Edge browser. Open the empty project folder in your editor; open the terminal there, not in this catalog repository. Verify: You can create a text file in the project folder and open browser developer tools. Cost: No paid service required for this local step. - Pipedrive acceptance sample: Create synthetic sample data before implementation: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Save it under fixtures/ with the expected results in fixtures/README.md; use no real credentials or customer records. Verify: The fixture files and expected outcomes exist and can be inspected without a vendor account. Cost: No paid service required for this local step. - Confirm the bounded replacement: The deliverable is a deal pipeline with dated activity and honest value summaries. Read every exclusion below. Indie mode runs locally; any public or shared use requires the product access and deployment gates first. Verify: You can name the primary workflow and the vendor features this version deliberately leaves out. Cost: No paid service required for this local step. - Configuration: DATA_DIR, SECRET_KEY, APP_MODE, SITE_URL. Ship .env.example, replace placeholders and exclude secrets from git. ### Phase 1 · Local foundation and data contract Build: Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. - Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Commands, after creating the named files: `python -m venv .venv`; `python -m pip install Flask Flask-WTF python-dotenv waitress tzdata`; `python -m pip freeze > requirements.txt`; `python -m flask --app app run --host 127.0.0.1`. - For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Commands, after creating the named files: `python manage.py init`; `python manage.py seed`. - Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. - Trap: The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. Done when: The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. Restarting preserves the seeded records or canonical files; running init again deletes nothing. A cross-origin state-changing request to an admin route is refused. Do not build yet: Do not start deals and stages until these checks pass. ### Phase 2 · Deals and stages Build: Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Move deals between stages in a transaction and append stage history; support won/lost states separately. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Money stored as floating point creates avoidable rounding errors. Done when: Moving a deal produces one dated event and preserves its amount. A negative deal amount fails validation. Do not build yet: Do not start next activities until these checks pass. ### Phase 3 · Next activities Build: Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. - Add call, meeting and follow-up activities with due time and completion history. - Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Recording a planned call is not proof that a call happened. Done when: Completing the last activity puts the still-open deal in no-next-action. A won deal is excluded from the open follow-up inbox. Do not build yet: Do not start pipeline reporting until these checks pass. ### Phase 4 · Pipeline reporting Build: Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Import/export deals and activities with stable ids and a merge preview for existing contacts. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Forecast probabilities must be user-defined and labelled estimates, not predictions. Done when: The fixture reports USD 350 and a separate EUR total, never a combined number. Reimporting the same exported deal ids does not duplicate revenue. Do not build yet: Do not start portable delivery and clean-start proof until these checks pass. ### Phase 5 · Portable delivery and clean-start proof Build: Finish the Pipedrive replacement with a documented first-run path and a recoverable export. - Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. - Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. - Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Commands, after creating the named files: `python -m pip install -r requirements.txt`; `python -m unittest discover -s test`. - Trap: Export without an import or restore rehearsal is not verified portability. Done when: A new folder reaches the documented fixture outcome using only README instructions. A backup restored in isolation preserves the proof data and can be opened. Do not build yet: Do not start operate and share with access controls until these checks pass. ### Phase 6 · Operate and share with access controls (product-builder only) Build: Product-builder only: make a deal pipeline with dated activity and honest value summaries operable for its stated audience before allowing remote access. - Add owner/member/viewer authorization as appropriate, password hashes through Werkzeug, expiring server-side sessions, CSRF and login rate limits. Add users, sessions and audit schema migrations plus an owner-init command prompting securely for its password. Enforce ownership on every private read/write/download and fail closed when product setup is incomplete. Existing learner or admin identities must use this same boundary. - Serve app:app with Waitress on loopback behind Caddy HTTPS. Configure trusted proxy headers narrowly, Secure/HttpOnly/SameSite cookies, upload limits, request ids and structured logs without private content. Run background jobs as a separate supervised process when the domain workflow requires them. Commands, after creating the named files: `waitress-serve --listen=127.0.0.1:5000 app:app`. - Add a scheduled encrypted off-host backup using this procedure: Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Monitor health, disk space, failed jobs and backup age. Stop the service to test an alert; rehearse recovery with outbound effects disabled and record recovery time. Rotate any exposed credentials and require reconciliation before resuming queues. - Trap: Product mode is additional engineering, not a switch that makes a local prototype production-ready. Done when: An unauthenticated visitor cannot read private records, download private files or mutate the admin surface. A viewer cannot mutate data by making a direct request, and guessed ids cannot cross ownership boundaries. Stopping the service triggers the configured alert and the latest off-host backup restores the fixture in isolation. Do not build yet: Do not add new providers or vendor-scale features until the release gates are recorded. ### Out of scope (and why) - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish: retain the paid product if this capability is essential; it is outside this bounded build. - automatic email and calendar capture: retain the paid product if this capability is essential; it is outside this bounded build. - data enrichment: retain the paid product if this capability is essential; it is outside this bounded build. - large integration ecosystem: retain the paid product if this capability is essential; it is outside this bounded build. - enterprise reporting: retain the paid product if this capability is essential; it is outside this bounded build. ### README must contain - Exact install, configure, initialize, start, test and recovery commands for a clean folder. - The schema, fixture, acceptance results, private data locations and export format. - Every prerequisite and secret source, actual running costs and deliberately excluded capabilities. - An honest distinction between tests actually run and checks still awaiting real credentials or deployment. - Dependency documentation reviewed 2026-09-05: https://flask.palletsprojects.com/en/stable/installation/ ; https://docs.python.org/3/library/sqlite3.html ; https://flask-wtf.readthedocs.io/en/1.2.x/csrf/ ; https://docs.pylonsproject.org/projects/waitress/en/stable/usage.html. Recheck before upgrading; freeze the versions actually tested. ===== ARCHITECTURE.md ===== # Architecture · Pipedrive ## Stack | Part | Choice | Why | | --- | --- | --- | | Runtime | Python 3.12+ and Flask | A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. | | Storage | SQLite through Python sqlite3 | Local ownership with explicit transactions and a portable backup path. | | Interface | Jinja HTML templates, CSS and vanilla JavaScript | Implement the specified screens directly with labelled controls and progressive enhancement. | | Verification | Python unittest and browser acceptance fixtures | Check invariants and the actual user workflow before the next phase. | ## Modules Each module has one owner concern and a documented way to replace it. | Module | Owns | How to replace it | | --- | --- | --- | | Data and identity | contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at) | Keep stable ids and a versioned repository interface; migrate storage behind it with a fixture round-trip. | | Deals and stages | Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. | Keep the acceptance contract: Moving a deal produces one dated event and preserves its amount. Replace only this module after replaying its fixture; preserve ids and existing records. | | Next activities | Add call, meeting and follow-up activities with due time and completion history. | Keep the acceptance contract: Completing the last activity puts the still-open deal in no-next-action. Replace only this module after replaying its fixture; preserve ids and existing records. | | Pipeline reporting | Report open totals by currency and stage; show won/lost changes over a chosen date range from events. | Keep the acceptance contract: The fixture reports USD 350 and a separate EUR total, never a combined number. Replace only this module after replaying its fixture; preserve ids and existing records. | | Operations | Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. | Change host or backup destination only after an isolated restore and authorization check. | ## Configuration Every runtime setting is an environment variable documented in `.env.example`, validated at startup, with a safe local default wherever one exists. - `DATA_DIR` · required · A new private folder this application creates on first run; never serve it as static files. - `SECRET_KEY` · required, secret · Generate with python -c "import secrets; print(secrets.token_hex(32))" and save only in .env. - `APP_MODE` · required · Use indie for loopback-only personal work. Product mode must refuse to start until owner login and the deployment gates are configured. - `SITE_URL` · required · The origin used for local forms and links; replace with the chosen HTTPS origin in product mode. ## Production baseline - Security: least privilege, input validation at every boundary, secret redaction in logs, rate limits on abuse-prone paths, no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore procedures that have been exercised. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, timeouts. - Observability: structured logs with request or operation ids, an error-tracking hook, and health and readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, one end-to-end test of the critical path. ## Decision records For each dependency in the stack table, keep a short note: why it was chosen, its failure mode, and how it is replaced. Do not add infrastructure until a requirement in `PRODUCT.md` justifies it. ===== AGENTS.md ===== # Agent instructions · Pipedrive product build - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. The stack is fixed: Python 3.12+ and Flask, SQLite through Python sqlite3, Jinja HTML templates, CSS and vanilla JavaScript, Python unittest and browser acceptance fixtures. - Implement milestone by milestone from `MILESTONES.md`; keep each change reviewable and leave the application runnable at every commit. - Treat authentication, payments, encryption, imports, webhooks and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a check pass. - Put every external service behind an interface with a deterministic fake for tests. - Add migrations and rollback or recovery notes for every persistent data change. - Log useful operational context without credentials, tokens, passwords or personal data. - Update documentation and run every check before completing a milestone. ## Known traps - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. - Money stored as floating point creates avoidable rounding errors. - Recording a planned call is not proof that a call happened. - Forecast probabilities must be user-defined and labelled estimates, not predictions. - Export without an import or restore rehearsal is not verified portability. - Product mode is additional engineering, not a switch that makes a local prototype production-ready. ===== MILESTONES.md ===== # Delivery milestones · Pipedrive Estimated effort: **multi-day** for the indie phases; the production-only milestones add the trust and operability layer. ## M1 · Local foundation and data contract Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. ### Steps 1. Create and start the local application Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Files: `app.py`, `requirements.txt`, `.env.example`, `.gitignore` ```sh python -m venv .venv python -m pip install Flask Flask-WTF python-dotenv waitress tzdata python -m pip freeze > requirements.txt python -m flask --app app run --host 127.0.0.1 ``` 2. Implement storage and seed the named fixture For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Files: `schema.sql`, `db.py`, `manage.py`, `fixtures/README.md` ```sh python manage.py init python manage.py seed ``` 3. Protect the local request boundary Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. Files: `app.py`, `templates/base.html`, `test/test_foundation.py` ### Done when - [ ] The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. - [ ] Restarting preserves the seeded records or canonical files; running init again deletes nothing. - [ ] A cross-origin state-changing request to an admin route is refused. ### Watch out - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. ## M2 · Deals and stages Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. ### Steps 1. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Files: `features/deals_and_stages.py`, `templates/deals_and_stages.html` 2. Move deals between stages in a transaction and append stage history; support won/lost states separately. Move deals between stages in a transaction and append stage history; support won/lost states separately. Files: `features/deals_and_stages.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_deals_and_stages.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Moving a deal produces one dated event and preserves its amount. - [ ] A negative deal amount fails validation. ### Watch out - Money stored as floating point creates avoidable rounding errors. ## M3 · Next activities Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. ### Steps 1. Add call, meeting and follow-up activities with due time and completion history. Add call, meeting and follow-up activities with due time and completion history. Files: `features/next_activities.py`, `templates/next_activities.html` 2. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Files: `features/next_activities.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_next_activities.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Completing the last activity puts the still-open deal in no-next-action. - [ ] A won deal is excluded from the open follow-up inbox. ### Watch out - Recording a planned call is not proof that a call happened. ## M4 · Pipeline reporting Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. ### Steps 1. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Files: `features/pipeline_reporting.py`, `templates/pipeline_reporting.html` 2. Import/export deals and activities with stable ids and a merge preview for existing contacts. Import/export deals and activities with stable ids and a merge preview for existing contacts. Files: `features/pipeline_reporting.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_pipeline_reporting.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] The fixture reports USD 350 and a separate EUR total, never a combined number. - [ ] Reimporting the same exported deal ids does not duplicate revenue. ### Watch out - Forecast probabilities must be user-defined and labelled estimates, not predictions. ## M5 · Portable delivery and clean-start proof Finish the Pipedrive replacement with a documented first-run path and a recoverable export. ### Steps 1. Write the user-facing runbook Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. Files: `README.md`, `.env.example` 2. Create and rehearse a recoverable backup Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. Files: `OPERATIONS.md`, `scripts/backup.py` 3. Reproduce the first-run experience Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Files: `README.md`, `verification.md` ```sh python -m pip install -r requirements.txt python -m unittest discover -s test ``` ### Done when - [ ] A new folder reaches the documented fixture outcome using only README instructions. - [ ] A backup restored in isolation preserves the proof data and can be opened. ### Watch out - Export without an import or restore rehearsal is not verified portability. ## M6 · Operate and share with access controls (production only) Product-builder only: make a deal pipeline with dated activity and honest value summaries operable for its stated audience before allowing remote access. ### Steps 1. Establish owner access before exposure Add owner/member/viewer authorization as appropriate, password hashes through Werkzeug, expiring server-side sessions, CSRF and login rate limits. Add users, sessions and audit schema migrations plus an owner-init command prompting securely for its password. Enforce ownership on every private read/write/download and fail closed when product setup is incomplete. Existing learner or admin identities must use this same boundary. Files: `ARCHITECTURE.md`, `OPERATIONS.md` 2. Deploy a monitored service Serve app:app with Waitress on loopback behind Caddy HTTPS. Configure trusted proxy headers narrowly, Secure/HttpOnly/SameSite cookies, upload limits, request ids and structured logs without private content. Run background jobs as a separate supervised process when the domain workflow requires them. Files: `Caddyfile`, `OPERATIONS.md` ```sh waitress-serve --listen=127.0.0.1:5000 app:app ``` 3. Rehearse loss and recovery Add a scheduled encrypted off-host backup using this procedure: Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Monitor health, disk space, failed jobs and backup age. Stop the service to test an alert; rehearse recovery with outbound effects disabled and record recovery time. Rotate any exposed credentials and require reconciliation before resuming queues. Files: `OPERATIONS.md`, `release-checklist.md` ### Done when - [ ] An unauthenticated visitor cannot read private records, download private files or mutate the admin surface. - [ ] A viewer cannot mutate data by making a direct request, and guessed ids cannot cross ownership boundaries. - [ ] Stopping the service triggers the configured alert and the latest off-host backup restores the fixture in isolation. ### Watch out - Product mode is additional engineering, not a switch that makes a local prototype production-ready. ===== OPERATIONS.md ===== # Operations · Pipedrive ## Backup Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. ## Restore Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. Do a restore drill before the first real user, and write the date here when it passes. ## Monitoring Check HTTP availability, free disk, backup age and domain failures for Deals and stages, Next activities, Pipeline reporting. Alert without logging private payloads. ## Incident checklist Pause outbound jobs and public intake as appropriate, preserve redacted diagnostics, restore an isolated verified backup, rotate affected credentials and reconcile uncertain effects before reopening. 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified backup when needed. 5. Document the root cause, the remediation and the regression test. ## Release gate - [ ] Moving a deal produces one dated event and preserves its amount. - [ ] Completing the last activity puts the still-open deal in no-next-action. - [ ] The fixture reports USD 350 and a separate EUR total, never a combined number. - [ ] A private-data authorization check passes using a second identity. - [ ] An off-host restore drill has a date, observed result and recovery time in OPERATIONS.md. - [ ] README names the excluded vendor capabilities and actual provider/hosting costs. ## Launch constraint Do not market omitted Pipedrive capabilities as implemented. The non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered. ===== .env.example ===== # Copy to .env and fill in. Never commit .env; this file documents it. # Required. A new private folder this application creates on first run; never serve it as static files. DATA_DIR=./data/pipedrive # Required · secret. Generate with python -c "import secrets; print(secrets.token_hex(32))" and save only in .env. SECRET_KEY=replace-with-a-random-secret # Required. Use indie for loopback-only personal work. Product mode must refuse to start until owner login and the deployment gates are configured. APP_MODE=indie # Required. The origin used for local forms and links; replace with the chosen HTTPS origin in product mode. SITE_URL=http://127.0.0.1:5000
README.md
# Pipedrive · indie build Build a deal pipeline with dated activity and honest value summaries. Estimated effort: **multi-day**. Work `BUILD_PLAN.md` top to bottom · every phase ends in a check that has to pass before the next one starts. ## Stack | Part | Choice | Why | | --- | --- | --- | | Runtime | Python 3.12+ and Flask | A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. | | Storage | SQLite through Python sqlite3 | Local ownership with explicit transactions and a portable backup path. | | Interface | Jinja HTML templates, CSS and vanilla JavaScript | Implement the specified screens directly with labelled controls and progressive enhancement. | | Verification | Python unittest and browser acceptance fixtures | Check invariants and the actual user workflow before the next phase. | ## Before you start Have every one of these ready. The plan assumes them from step one. - [ ] **Python 3.12 or newer and a terminal** · Python is free; this local prototype requires no hosting subscription. - Why: The local backend, tests and storage use Python. - Get it: Install Python from python.org. Open a terminal in a new empty project folder. On Windows, use py -3 where this guide says python if python is not on PATH; on macOS/Linux use python3 if needed. Create .venv and activate it before installing packages. - Verify: python --version reports 3.12+ and python -c "import sqlite3" succeeds. - [ ] **A current desktop browser and text editor** · No paid service required for this local step. - Why: You need to view the local interface and edit generated project files. - Get it: Use an installed Chrome, Firefox or Edge browser. Open the empty project folder in your editor; open the terminal there, not in this catalog repository. - Verify: You can create a text file in the project folder and open browser developer tools. - [ ] **Pipedrive acceptance sample** · No paid service required for this local step. - Why: This fixture makes the first end-to-end check reproducible. - Get it: Create synthetic sample data before implementation: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Save it under fixtures/ with the expected results in fixtures/README.md; use no real credentials or customer records. - Verify: The fixture files and expected outcomes exist and can be inspected without a vendor account. - [ ] **Confirm the bounded replacement** · No paid service required for this local step. - Why: The full commercial product is larger than this guide. - Get it: The deliverable is a deal pipeline with dated activity and honest value summaries. Read every exclusion below. Indie mode runs locally; any public or shared use requires the product access and deployment gates first. - Verify: You can name the primary workflow and the vendor features this version deliberately leaves out. ## Quick start ```sh python -m venv .venv python -m pip install Flask Flask-WTF python-dotenv waitress tzdata python -m pip freeze > requirements.txt python -m flask --app app run --host 127.0.0.1 ``` Then copy `.env.example` to `.env` and fill in the values it documents. ## Honest limits This build deliberately does not replace: - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish - automatic email and calendar capture - data enrichment - large integration ecosystem - enterprise reporting If one of those is essential to you, that is the reason to keep paying for Pipedrive, and the README should say so rather than pretend.
BRIEF.md
# Build brief · Pipedrive The one-shot brief this plan expands. `BUILD_PLAN.md` (or `MILESTONES.md`) is the same sequence broken into steps and checks; where the two disagree, the plan wins. Build me a deal pipeline with dated activity and honest value summaries as a bounded replacement for Pipedrive. Build it in phases in the order below. Do not write the whole product in one pass. Finish the current phase, run its Done when checks, fix failures, then continue. Indie mode completes Phases 1-5. Phase 6 is required before shared or public deployment. ### Stack (fixed, do not substitute) - Runtime: Python 3.12+ and Flask. A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. - Storage: SQLite through Python sqlite3. Local ownership with explicit transactions and a portable backup path. - Interface: Jinja HTML templates, CSS and vanilla JavaScript. Implement the specified screens directly with labelled controls and progressive enhancement. - Verification: Python unittest and browser acceptance fixtures. Check invariants and the actual user workflow before the next phase. ### Data model (create this before Phase 1) - contacts(id,name,email) - stages(id,name,position) - deals(id,contact_id,title,amount_minor,currency,stage_id,state) - activities(id,deal_id,due_at,type,done) - stage_events(id,deal_id,from_stage,to_stage,at) - Use stable ids and explicit relationships; add auxiliary tables named by the phases before those phases use them. - Acceptance fixture: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. ### Prerequisites and configuration - Python 3.12 or newer and a terminal: Install Python from python.org. Open a terminal in a new empty project folder. On Windows, use py -3 where this guide says python if python is not on PATH; on macOS/Linux use python3 if needed. Create .venv and activate it before installing packages. Verify: python --version reports 3.12+ and python -c "import sqlite3" succeeds. Cost: Python is free; this local prototype requires no hosting subscription. - A current desktop browser and text editor: Use an installed Chrome, Firefox or Edge browser. Open the empty project folder in your editor; open the terminal there, not in this catalog repository. Verify: You can create a text file in the project folder and open browser developer tools. Cost: No paid service required for this local step. - Pipedrive acceptance sample: Create synthetic sample data before implementation: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Save it under fixtures/ with the expected results in fixtures/README.md; use no real credentials or customer records. Verify: The fixture files and expected outcomes exist and can be inspected without a vendor account. Cost: No paid service required for this local step. - Confirm the bounded replacement: The deliverable is a deal pipeline with dated activity and honest value summaries. Read every exclusion below. Indie mode runs locally; any public or shared use requires the product access and deployment gates first. Verify: You can name the primary workflow and the vendor features this version deliberately leaves out. Cost: No paid service required for this local step. - Configuration: DATA_DIR, SECRET_KEY, APP_MODE, SITE_URL. Ship .env.example, replace placeholders and exclude secrets from git. ### Phase 1 · Local foundation and data contract Build: Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. - Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Commands, after creating the named files: `python -m venv .venv`; `python -m pip install Flask Flask-WTF python-dotenv waitress tzdata`; `python -m pip freeze > requirements.txt`; `python -m flask --app app run --host 127.0.0.1`. - For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Commands, after creating the named files: `python manage.py init`; `python manage.py seed`. - Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. - Trap: The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. Done when: The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. Restarting preserves the seeded records or canonical files; running init again deletes nothing. A cross-origin state-changing request to an admin route is refused. Do not build yet: Do not start deals and stages until these checks pass. ### Phase 2 · Deals and stages Build: Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Move deals between stages in a transaction and append stage history; support won/lost states separately. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Money stored as floating point creates avoidable rounding errors. Done when: Moving a deal produces one dated event and preserves its amount. A negative deal amount fails validation. Do not build yet: Do not start next activities until these checks pass. ### Phase 3 · Next activities Build: Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. - Add call, meeting and follow-up activities with due time and completion history. - Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Recording a planned call is not proof that a call happened. Done when: Completing the last activity puts the still-open deal in no-next-action. A won deal is excluded from the open follow-up inbox. Do not build yet: Do not start pipeline reporting until these checks pass. ### Phase 4 · Pipeline reporting Build: Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Import/export deals and activities with stable ids and a merge preview for existing contacts. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Forecast probabilities must be user-defined and labelled estimates, not predictions. Done when: The fixture reports USD 350 and a separate EUR total, never a combined number. Reimporting the same exported deal ids does not duplicate revenue. Do not build yet: Do not start portable delivery and clean-start proof until these checks pass. ### Phase 5 · Portable delivery and clean-start proof Build: Finish the Pipedrive replacement with a documented first-run path and a recoverable export. - Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. - Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. - Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Commands, after creating the named files: `python -m pip install -r requirements.txt`; `python -m unittest discover -s test`. - Trap: Export without an import or restore rehearsal is not verified portability. Done when: A new folder reaches the documented fixture outcome using only README instructions. A backup restored in isolation preserves the proof data and can be opened. Do not build yet: Do not start operate and share with access controls until these checks pass. ### Phase 6 · Operate and share with access controls (product-builder only) Build: Product-builder only: make a deal pipeline with dated activity and honest value summaries operable for its stated audience before allowing remote access. - Add owner/member/viewer authorization as appropriate, password hashes through Werkzeug, expiring server-side sessions, CSRF and login rate limits. Add users, sessions and audit schema migrations plus an owner-init command prompting securely for its password. Enforce ownership on every private read/write/download and fail closed when product setup is incomplete. Existing learner or admin identities must use this same boundary. - Serve app:app with Waitress on loopback behind Caddy HTTPS. Configure trusted proxy headers narrowly, Secure/HttpOnly/SameSite cookies, upload limits, request ids and structured logs without private content. Run background jobs as a separate supervised process when the domain workflow requires them. Commands, after creating the named files: `waitress-serve --listen=127.0.0.1:5000 app:app`. - Add a scheduled encrypted off-host backup using this procedure: Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Monitor health, disk space, failed jobs and backup age. Stop the service to test an alert; rehearse recovery with outbound effects disabled and record recovery time. Rotate any exposed credentials and require reconciliation before resuming queues. - Trap: Product mode is additional engineering, not a switch that makes a local prototype production-ready. Done when: An unauthenticated visitor cannot read private records, download private files or mutate the admin surface. A viewer cannot mutate data by making a direct request, and guessed ids cannot cross ownership boundaries. Stopping the service triggers the configured alert and the latest off-host backup restores the fixture in isolation. Do not build yet: Do not add new providers or vendor-scale features until the release gates are recorded. ### Out of scope (and why) - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish: retain the paid product if this capability is essential; it is outside this bounded build. - automatic email and calendar capture: retain the paid product if this capability is essential; it is outside this bounded build. - data enrichment: retain the paid product if this capability is essential; it is outside this bounded build. - large integration ecosystem: retain the paid product if this capability is essential; it is outside this bounded build. - enterprise reporting: retain the paid product if this capability is essential; it is outside this bounded build. ### README must contain - Exact install, configure, initialize, start, test and recovery commands for a clean folder. - The schema, fixture, acceptance results, private data locations and export format. - Every prerequisite and secret source, actual running costs and deliberately excluded capabilities. - An honest distinction between tests actually run and checks still awaiting real credentials or deployment. - Dependency documentation reviewed 2026-09-05: https://flask.palletsprojects.com/en/stable/installation/ ; https://docs.python.org/3/library/sqlite3.html ; https://flask-wtf.readthedocs.io/en/1.2.x/csrf/ ; https://docs.pylonsproject.org/projects/waitress/en/stable/usage.html. Recheck before upgrading; freeze the versions actually tested.
AGENTS.md
# Agent instructions · Pipedrive indie build - Read `README.md` and `BUILD_PLAN.md` before writing code. The stack is fixed: Python 3.12+ and Flask, SQLite through Python sqlite3, Jinja HTML templates, CSS and vanilla JavaScript, Python unittest and browser acceptance fixtures. Do not substitute. - Work one phase at a time, in order. Do not start a phase until every "Done when" item of the previous one passes. - Prefer the fewest moving parts that satisfy the step. No frameworks, services or dependencies the plan does not name. - Secrets live in `.env`, never in source or logs. Keep `.env.example` current when a variable is introduced. - Do not invent cryptography, security guarantees, APIs or compliance claims. - Add a focused test for every destructive, security-sensitive or data-loss path the plan names. - Run the project checks before declaring a phase complete, and record any deliberate shortcut in the README under "Tradeoffs". ## Known traps - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. - Money stored as floating point creates avoidable rounding errors. - Recording a planned call is not proof that a call happened. - Forecast probabilities must be user-defined and labelled estimates, not predictions. - Export without an import or restore rehearsal is not verified portability.
BUILD_PLAN.md
# Build plan · Pipedrive Build a deal pipeline with dated activity and honest value summaries. Phases are in dependency order. Each ends in a "Done when" list; treat an unticked item as a blocker, not a note. ## Phase 1 · Local foundation and data contract Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. ### Steps 1. Create and start the local application Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Files: `app.py`, `requirements.txt`, `.env.example`, `.gitignore` ```sh python -m venv .venv python -m pip install Flask Flask-WTF python-dotenv waitress tzdata python -m pip freeze > requirements.txt python -m flask --app app run --host 127.0.0.1 ``` 2. Implement storage and seed the named fixture For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Files: `schema.sql`, `db.py`, `manage.py`, `fixtures/README.md` ```sh python manage.py init python manage.py seed ``` 3. Protect the local request boundary Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. Files: `app.py`, `templates/base.html`, `test/test_foundation.py` ### Done when - [ ] The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. - [ ] Restarting preserves the seeded records or canonical files; running init again deletes nothing. - [ ] A cross-origin state-changing request to an admin route is refused. ### Watch out - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. ## Phase 2 · Deals and stages Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. ### Steps 1. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Files: `features/deals_and_stages.py`, `templates/deals_and_stages.html` 2. Move deals between stages in a transaction and append stage history; support won/lost states separately. Move deals between stages in a transaction and append stage history; support won/lost states separately. Files: `features/deals_and_stages.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_deals_and_stages.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Moving a deal produces one dated event and preserves its amount. - [ ] A negative deal amount fails validation. ### Watch out - Money stored as floating point creates avoidable rounding errors. ## Phase 3 · Next activities Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. ### Steps 1. Add call, meeting and follow-up activities with due time and completion history. Add call, meeting and follow-up activities with due time and completion history. Files: `features/next_activities.py`, `templates/next_activities.html` 2. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Files: `features/next_activities.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_next_activities.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Completing the last activity puts the still-open deal in no-next-action. - [ ] A won deal is excluded from the open follow-up inbox. ### Watch out - Recording a planned call is not proof that a call happened. ## Phase 4 · Pipeline reporting Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. ### Steps 1. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Files: `features/pipeline_reporting.py`, `templates/pipeline_reporting.html` 2. Import/export deals and activities with stable ids and a merge preview for existing contacts. Import/export deals and activities with stable ids and a merge preview for existing contacts. Files: `features/pipeline_reporting.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_pipeline_reporting.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] The fixture reports USD 350 and a separate EUR total, never a combined number. - [ ] Reimporting the same exported deal ids does not duplicate revenue. ### Watch out - Forecast probabilities must be user-defined and labelled estimates, not predictions. ## Phase 5 · Portable delivery and clean-start proof Finish the Pipedrive replacement with a documented first-run path and a recoverable export. ### Steps 1. Write the user-facing runbook Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. Files: `README.md`, `.env.example` 2. Create and rehearse a recoverable backup Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. Files: `OPERATIONS.md`, `scripts/backup.py` 3. Reproduce the first-run experience Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Files: `README.md`, `verification.md` ```sh python -m pip install -r requirements.txt python -m unittest discover -s test ``` ### Done when - [ ] A new folder reaches the documented fixture outcome using only README instructions. - [ ] A backup restored in isolation preserves the proof data and can be opened. ### Watch out - Export without an import or restore rehearsal is not verified portability. ## Not in this build - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish - automatic email and calendar capture - data enrichment - large integration ecosystem - enterprise reporting ## After v1, if you want it - Extend pipeline reporting only after the fixture and recovery checks pass. - Before adding another integration, document its credentials, limits, cost and failure behavior with primary-source links.
.env.example
# Copy to .env and fill in. Never commit .env; this file documents it. # Required. A new private folder this application creates on first run; never serve it as static files. DATA_DIR=./data/pipedrive # Required · secret. Generate with python -c "import secrets; print(secrets.token_hex(32))" and save only in .env. SECRET_KEY=replace-with-a-random-secret # Required. Use indie for loopback-only personal work. Product mode must refuse to start until owner login and the deployment gates are configured. APP_MODE=indie # Required. The origin used for local forms and links; replace with the chosen HTTPS origin in product mode. SITE_URL=http://127.0.0.1:5000
PRODUCT.md
# Pipedrive · product brief ## Problem The core loop is buildable, but a dependable replacement becomes a real weekend or multi-day project. For Pipedrive, manage contacts and deals through a visual pipeline with activities and reminders. The hard boundary is email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish, plus integrations, data quality, and workflow lock-in. ## Product outcome An operated version of a deal pipeline with dated activity and honest value summaries, with authorized access, restore evidence and honest scope limits. ## Target user A builder who needs a maintainable product foundation, not a one-off demo. ## Required capabilities - Docker - PostgreSQL - self-hosted server - optional email API credentials ## Explicit non-goals for v1 - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish - automatic email and calendar capture - data enrichment - large integration ecosystem - enterprise reporting ## Success criteria - Moving a deal produces one dated event and preserves its amount. - Completing the last activity puts the still-open deal in no-next-action. - The fixture reports USD 350 and a separate EUR total, never a combined number. - A private-data authorization check passes using a second identity. - An off-host restore drill has a date, observed result and recovery time in OPERATIONS.md. - README names the excluded vendor capabilities and actual provider/hosting costs.
BRIEF.md
# Build brief · Pipedrive The one-shot brief this plan expands. `BUILD_PLAN.md` (or `MILESTONES.md`) is the same sequence broken into steps and checks; where the two disagree, the plan wins. Build me a deal pipeline with dated activity and honest value summaries as a bounded replacement for Pipedrive. Build it in phases in the order below. Do not write the whole product in one pass. Finish the current phase, run its Done when checks, fix failures, then continue. Indie mode completes Phases 1-5. Phase 6 is required before shared or public deployment. ### Stack (fixed, do not substitute) - Runtime: Python 3.12+ and Flask. A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. - Storage: SQLite through Python sqlite3. Local ownership with explicit transactions and a portable backup path. - Interface: Jinja HTML templates, CSS and vanilla JavaScript. Implement the specified screens directly with labelled controls and progressive enhancement. - Verification: Python unittest and browser acceptance fixtures. Check invariants and the actual user workflow before the next phase. ### Data model (create this before Phase 1) - contacts(id,name,email) - stages(id,name,position) - deals(id,contact_id,title,amount_minor,currency,stage_id,state) - activities(id,deal_id,due_at,type,done) - stage_events(id,deal_id,from_stage,to_stage,at) - Use stable ids and explicit relationships; add auxiliary tables named by the phases before those phases use them. - Acceptance fixture: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. ### Prerequisites and configuration - Python 3.12 or newer and a terminal: Install Python from python.org. Open a terminal in a new empty project folder. On Windows, use py -3 where this guide says python if python is not on PATH; on macOS/Linux use python3 if needed. Create .venv and activate it before installing packages. Verify: python --version reports 3.12+ and python -c "import sqlite3" succeeds. Cost: Python is free; this local prototype requires no hosting subscription. - A current desktop browser and text editor: Use an installed Chrome, Firefox or Edge browser. Open the empty project folder in your editor; open the terminal there, not in this catalog repository. Verify: You can create a text file in the project folder and open browser developer tools. Cost: No paid service required for this local step. - Pipedrive acceptance sample: Create synthetic sample data before implementation: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Save it under fixtures/ with the expected results in fixtures/README.md; use no real credentials or customer records. Verify: The fixture files and expected outcomes exist and can be inspected without a vendor account. Cost: No paid service required for this local step. - Confirm the bounded replacement: The deliverable is a deal pipeline with dated activity and honest value summaries. Read every exclusion below. Indie mode runs locally; any public or shared use requires the product access and deployment gates first. Verify: You can name the primary workflow and the vendor features this version deliberately leaves out. Cost: No paid service required for this local step. - Configuration: DATA_DIR, SECRET_KEY, APP_MODE, SITE_URL. Ship .env.example, replace placeholders and exclude secrets from git. ### Phase 1 · Local foundation and data contract Build: Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. - Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Commands, after creating the named files: `python -m venv .venv`; `python -m pip install Flask Flask-WTF python-dotenv waitress tzdata`; `python -m pip freeze > requirements.txt`; `python -m flask --app app run --host 127.0.0.1`. - For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Commands, after creating the named files: `python manage.py init`; `python manage.py seed`. - Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. - Trap: The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. Done when: The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. Restarting preserves the seeded records or canonical files; running init again deletes nothing. A cross-origin state-changing request to an admin route is refused. Do not build yet: Do not start deals and stages until these checks pass. ### Phase 2 · Deals and stages Build: Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. - Move deals between stages in a transaction and append stage history; support won/lost states separately. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Money stored as floating point creates avoidable rounding errors. Done when: Moving a deal produces one dated event and preserves its amount. A negative deal amount fails validation. Do not build yet: Do not start next activities until these checks pass. ### Phase 3 · Next activities Build: Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. - Add call, meeting and follow-up activities with due time and completion history. - Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Recording a planned call is not proof that a call happened. Done when: Completing the last activity puts the still-open deal in no-next-action. A won deal is excluded from the open follow-up inbox. Do not build yet: Do not start pipeline reporting until these checks pass. ### Phase 4 · Pipeline reporting Build: Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Report open totals by currency and stage; show won/lost changes over a chosen date range from events. - Import/export deals and activities with stable ids and a merge preview for existing contacts. - Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Commands, after creating the named files: `python -m unittest discover -s test`. - Trap: Forecast probabilities must be user-defined and labelled estimates, not predictions. Done when: The fixture reports USD 350 and a separate EUR total, never a combined number. Reimporting the same exported deal ids does not duplicate revenue. Do not build yet: Do not start portable delivery and clean-start proof until these checks pass. ### Phase 5 · Portable delivery and clean-start proof Build: Finish the Pipedrive replacement with a documented first-run path and a recoverable export. - Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. - Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. - Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Commands, after creating the named files: `python -m pip install -r requirements.txt`; `python -m unittest discover -s test`. - Trap: Export without an import or restore rehearsal is not verified portability. Done when: A new folder reaches the documented fixture outcome using only README instructions. A backup restored in isolation preserves the proof data and can be opened. Do not build yet: Do not start operate and share with access controls until these checks pass. ### Phase 6 · Operate and share with access controls (product-builder only) Build: Product-builder only: make a deal pipeline with dated activity and honest value summaries operable for its stated audience before allowing remote access. - Add owner/member/viewer authorization as appropriate, password hashes through Werkzeug, expiring server-side sessions, CSRF and login rate limits. Add users, sessions and audit schema migrations plus an owner-init command prompting securely for its password. Enforce ownership on every private read/write/download and fail closed when product setup is incomplete. Existing learner or admin identities must use this same boundary. - Serve app:app with Waitress on loopback behind Caddy HTTPS. Configure trusted proxy headers narrowly, Secure/HttpOnly/SameSite cookies, upload limits, request ids and structured logs without private content. Run background jobs as a separate supervised process when the domain workflow requires them. Commands, after creating the named files: `waitress-serve --listen=127.0.0.1:5000 app:app`. - Add a scheduled encrypted off-host backup using this procedure: Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Monitor health, disk space, failed jobs and backup age. Stop the service to test an alert; rehearse recovery with outbound effects disabled and record recovery time. Rotate any exposed credentials and require reconciliation before resuming queues. - Trap: Product mode is additional engineering, not a switch that makes a local prototype production-ready. Done when: An unauthenticated visitor cannot read private records, download private files or mutate the admin surface. A viewer cannot mutate data by making a direct request, and guessed ids cannot cross ownership boundaries. Stopping the service triggers the configured alert and the latest off-host backup restores the fixture in isolation. Do not build yet: Do not add new providers or vendor-scale features until the release gates are recorded. ### Out of scope (and why) - This is a deal pipeline with dated activity and honest value summaries; full Pipedrive feature parity, vendor hosting and support are not included. - email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish: retain the paid product if this capability is essential; it is outside this bounded build. - automatic email and calendar capture: retain the paid product if this capability is essential; it is outside this bounded build. - data enrichment: retain the paid product if this capability is essential; it is outside this bounded build. - large integration ecosystem: retain the paid product if this capability is essential; it is outside this bounded build. - enterprise reporting: retain the paid product if this capability is essential; it is outside this bounded build. ### README must contain - Exact install, configure, initialize, start, test and recovery commands for a clean folder. - The schema, fixture, acceptance results, private data locations and export format. - Every prerequisite and secret source, actual running costs and deliberately excluded capabilities. - An honest distinction between tests actually run and checks still awaiting real credentials or deployment. - Dependency documentation reviewed 2026-09-05: https://flask.palletsprojects.com/en/stable/installation/ ; https://docs.python.org/3/library/sqlite3.html ; https://flask-wtf.readthedocs.io/en/1.2.x/csrf/ ; https://docs.pylonsproject.org/projects/waitress/en/stable/usage.html. Recheck before upgrading; freeze the versions actually tested.
ARCHITECTURE.md
# Architecture · Pipedrive ## Stack | Part | Choice | Why | | --- | --- | --- | | Runtime | Python 3.12+ and Flask | A small local HTTP application with readable server-side handlers and no JavaScript build pipeline. | | Storage | SQLite through Python sqlite3 | Local ownership with explicit transactions and a portable backup path. | | Interface | Jinja HTML templates, CSS and vanilla JavaScript | Implement the specified screens directly with labelled controls and progressive enhancement. | | Verification | Python unittest and browser acceptance fixtures | Check invariants and the actual user workflow before the next phase. | ## Modules Each module has one owner concern and a documented way to replace it. | Module | Owns | How to replace it | | --- | --- | --- | | Data and identity | contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at) | Keep stable ids and a versioned repository interface; migrate storage behind it with a fixture round-trip. | | Deals and stages | Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. | Keep the acceptance contract: Moving a deal produces one dated event and preserves its amount. Replace only this module after replaying its fixture; preserve ids and existing records. | | Next activities | Add call, meeting and follow-up activities with due time and completion history. | Keep the acceptance contract: Completing the last activity puts the still-open deal in no-next-action. Replace only this module after replaying its fixture; preserve ids and existing records. | | Pipeline reporting | Report open totals by currency and stage; show won/lost changes over a chosen date range from events. | Keep the acceptance contract: The fixture reports USD 350 and a separate EUR total, never a combined number. Replace only this module after replaying its fixture; preserve ids and existing records. | | Operations | Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. | Change host or backup destination only after an isolated restore and authorization check. | ## Configuration Every runtime setting is an environment variable documented in `.env.example`, validated at startup, with a safe local default wherever one exists. - `DATA_DIR` · required · A new private folder this application creates on first run; never serve it as static files. - `SECRET_KEY` · required, secret · Generate with python -c "import secrets; print(secrets.token_hex(32))" and save only in .env. - `APP_MODE` · required · Use indie for loopback-only personal work. Product mode must refuse to start until owner login and the deployment gates are configured. - `SITE_URL` · required · The origin used for local forms and links; replace with the chosen HTTPS origin in product mode. ## Production baseline - Security: least privilege, input validation at every boundary, secret redaction in logs, rate limits on abuse-prone paths, no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore procedures that have been exercised. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, timeouts. - Observability: structured logs with request or operation ids, an error-tracking hook, and health and readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, one end-to-end test of the critical path. ## Decision records For each dependency in the stack table, keep a short note: why it was chosen, its failure mode, and how it is replaced. Do not add infrastructure until a requirement in `PRODUCT.md` justifies it.
AGENTS.md
# Agent instructions · Pipedrive product build - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. The stack is fixed: Python 3.12+ and Flask, SQLite through Python sqlite3, Jinja HTML templates, CSS and vanilla JavaScript, Python unittest and browser acceptance fixtures. - Implement milestone by milestone from `MILESTONES.md`; keep each change reviewable and leave the application runnable at every commit. - Treat authentication, payments, encryption, imports, webhooks and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a check pass. - Put every external service behind an interface with a deterministic fake for tests. - Add migrations and rollback or recovery notes for every persistent data change. - Log useful operational context without credentials, tokens, passwords or personal data. - Update documentation and run every check before completing a milestone. ## Known traps - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. - Money stored as floating point creates avoidable rounding errors. - Recording a planned call is not proof that a call happened. - Forecast probabilities must be user-defined and labelled estimates, not predictions. - Export without an import or restore rehearsal is not verified portability. - Product mode is additional engineering, not a switch that makes a local prototype production-ready.
MILESTONES.md
# Delivery milestones · Pipedrive Estimated effort: **multi-day** for the indie phases; the production-only milestones add the trust and operability layer. ## M1 · Local foundation and data contract Create the runnable local foundation for a deal pipeline with dated activity and honest value summaries, including the real schema and acceptance fixture. ### Steps 1. Create and start the local application Run the venv command first, then stop and activate it before running the remaining commands. Use your OS instructions: Windows .venv\Scripts\activate.bat in cmd, or .venv\Scripts\Activate.ps1 in PowerShell; macOS/Linux source .venv/bin/activate. Then install the listed packages. Create app.py exposing app, load .env with python-dotenv, and add a /healthz route. Freeze tested dependency versions to requirements.txt. Create .env manually from .env.example; replace SECRET_KEY before launch. Files: `app.py`, `requirements.txt`, `.env.example`, `.gitignore` ```sh python -m venv .venv python -m pip install Flask Flask-WTF python-dotenv waitress tzdata python -m pip freeze > requirements.txt python -m flask --app app run --host 127.0.0.1 ``` 2. Implement storage and seed the named fixture For database-backed state create schema.sql and db.py using this model: contacts(id,name,email); stages(id,name,position); deals(id,contact_id,title,amount_minor,currency,stage_id,state); activities(id,deal_id,due_at,type,done); stage_events(id,deal_id,from_stage,to_stage,at). Add the auxiliary relationships explicitly used in later phases; use stable ids, foreign keys, parameterized values and transactions. For canonical files use atomic replacement and hashes instead. Implement python manage.py init and python manage.py seed to create only synthetic data: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Re-running init must not erase data. Files: `schema.sql`, `db.py`, `manage.py`, `fixtures/README.md` ```sh python manage.py init python manage.py seed ``` 3. Protect the local request boundary Install Flask-WTF CSRF protection for forms and same-origin fetches, validate Host and Origin against SITE_URL, bound inputs and escape output. Deliberately public intake endpoints get bounded validation and rate limits; signed provider webhooks use signature checks instead of browser CSRF tokens. All other admin routes stay local until product authentication exists. When a later phase tests viewer/member permissions, implement the users, hashed passwords, expiring server sessions and role checks in this foundation first; product mode must never use a fabricated identity from request input. Add error, empty, keyboard-focus and retry states now. Files: `app.py`, `templates/base.html`, `test/test_foundation.py` ### Done when - [ ] The documented start command serves /healthz and the initial screen at http://127.0.0.1:5000. - [ ] Restarting preserves the seeded records or canonical files; running init again deletes nothing. - [ ] A cross-origin state-changing request to an admin route is refused. ### Watch out - The Flask development server is for local development only. Loopback binding alone does not replace CSRF and origin validation. ## M2 · Deals and stages Deals and stages for Pipedrive: Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. ### Steps 1. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Create contacts, ordered stages and deals with integer minor-unit amounts and explicit currency. Files: `features/deals_and_stages.py`, `templates/deals_and_stages.html` 2. Move deals between stages in a transaction and append stage history; support won/lost states separately. Move deals between stages in a transaction and append stage history; support won/lost states separately. Files: `features/deals_and_stages.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Moving a deal produces one dated event and preserves its amount. Then check: A negative deal amount fails validation. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_deals_and_stages.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Moving a deal produces one dated event and preserves its amount. - [ ] A negative deal amount fails validation. ### Watch out - Money stored as floating point creates avoidable rounding errors. ## M3 · Next activities Next activities for Pipedrive: Add call, meeting and follow-up activities with due time and completion history. ### Steps 1. Add call, meeting and follow-up activities with due time and completion history. Add call, meeting and follow-up activities with due time and completion history. Files: `features/next_activities.py`, `templates/next_activities.html` 2. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Create a no-next-action filter for open deals and an overdue activity inbox with direct deal links. Files: `features/next_activities.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: Completing the last activity puts the still-open deal in no-next-action. Then check: A won deal is excluded from the open follow-up inbox. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_next_activities.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] Completing the last activity puts the still-open deal in no-next-action. - [ ] A won deal is excluded from the open follow-up inbox. ### Watch out - Recording a planned call is not proof that a call happened. ## M4 · Pipeline reporting Pipeline reporting for Pipedrive: Report open totals by currency and stage; show won/lost changes over a chosen date range from events. ### Steps 1. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Report open totals by currency and stage; show won/lost changes over a chosen date range from events. Files: `features/pipeline_reporting.py`, `templates/pipeline_reporting.html` 2. Import/export deals and activities with stable ids and a merge preview for existing contacts. Import/export deals and activities with stable ids and a merge preview for existing contacts. Files: `features/pipeline_reporting.py` 3. Exercise the acceptance fixture Use Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Check: The fixture reports USD 350 and a separate EUR total, never a combined number. Then check: Reimporting the same exported deal ids does not duplicate revenue. Add a focused regression for the failure case under test/ using a temporary database or folder and fake external services; also perform the visible workflow in a browser. Files: `test/test_pipeline_reporting.py` ```sh python -m unittest discover -s test ``` ### Done when - [ ] The fixture reports USD 350 and a separate EUR total, never a combined number. - [ ] Reimporting the same exported deal ids does not duplicate revenue. ### Watch out - Forecast probabilities must be user-defined and labelled estimates, not predictions. ## M5 · Portable delivery and clean-start proof Finish the Pipedrive replacement with a documented first-run path and a recoverable export. ### Steps 1. Write the user-facing runbook Document prerequisites, every configuration variable, data locations and the three domain workflows: Deals and stages; Next activities; Pipeline reporting. Include the exclusions, actual costs and source check date 2026-09-05. Commands shown earlier that reference project files are files the builder must implement before running them. Files: `README.md`, `.env.example` 2. Create and rehearse a recoverable backup Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. Files: `OPERATIONS.md`, `scripts/backup.py` 3. Reproduce the first-run experience Use a new folder and only README instructions to reach the fixture outcome. Install from requirements.txt, initialize storage, run the tests and exercise the UI at 375px and 1280px; use keyboard-only controls and inspect browser errors. Record exactly what passed; do not mark unrun checks complete. Files: `README.md`, `verification.md` ```sh python -m pip install -r requirements.txt python -m unittest discover -s test ``` ### Done when - [ ] A new folder reaches the documented fixture outcome using only README instructions. - [ ] A backup restored in isolation preserves the proof data and can be opened. ### Watch out - Export without an import or restore rehearsal is not verified portability. ## M6 · Operate and share with access controls (production only) Product-builder only: make a deal pipeline with dated activity and honest value summaries operable for its stated audience before allowing remote access. ### Steps 1. Establish owner access before exposure Add owner/member/viewer authorization as appropriate, password hashes through Werkzeug, expiring server-side sessions, CSRF and login rate limits. Add users, sessions and audit schema migrations plus an owner-init command prompting securely for its password. Enforce ownership on every private read/write/download and fail closed when product setup is incomplete. Existing learner or admin identities must use this same boundary. Files: `ARCHITECTURE.md`, `OPERATIONS.md` 2. Deploy a monitored service Serve app:app with Waitress on loopback behind Caddy HTTPS. Configure trusted proxy headers narrowly, Secure/HttpOnly/SameSite cookies, upload limits, request ids and structured logs without private content. Run background jobs as a separate supervised process when the domain workflow requires them. Files: `Caddyfile`, `OPERATIONS.md` ```sh waitress-serve --listen=127.0.0.1:5000 app:app ``` 3. Rehearse loss and recovery Add a scheduled encrypted off-host backup using this procedure: Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. Monitor health, disk space, failed jobs and backup age. Stop the service to test an alert; rehearse recovery with outbound effects disabled and record recovery time. Rotate any exposed credentials and require reconciliation before resuming queues. Files: `OPERATIONS.md`, `release-checklist.md` ### Done when - [ ] An unauthenticated visitor cannot read private records, download private files or mutate the admin surface. - [ ] A viewer cannot mutate data by making a direct request, and guessed ids cannot cross ownership boundaries. - [ ] Stopping the service triggers the configured alert and the latest off-host backup restores the fixture in isolation. ### Watch out - Product mode is additional engineering, not a switch that makes a local prototype production-ready.
OPERATIONS.md
# Operations · Pipedrive ## Backup Use sqlite3.Connection.backup for the database in DATA_DIR and pause writers while taking the matching attachment snapshot. Keep schema version, hashes and a manifest for pipedrive. ## Restore Restore into a separate empty directory or isolated deployment, with all outbound actions and schedules disabled. Recreate this proof: Two open USD deals worth 100 and 250, one EUR deal and an overdue call. Compare ids/counts and open the result before recording the restore date. Never test a restore over the only live copy. Do a restore drill before the first real user, and write the date here when it passes. ## Monitoring Check HTTP availability, free disk, backup age and domain failures for Deals and stages, Next activities, Pipeline reporting. Alert without logging private payloads. ## Incident checklist Pause outbound jobs and public intake as appropriate, preserve redacted diagnostics, restore an isolated verified backup, rotate affected credentials and reconcile uncertain effects before reopening. 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified backup when needed. 5. Document the root cause, the remediation and the regression test. ## Release gate - [ ] Moving a deal produces one dated event and preserves its amount. - [ ] Completing the last activity puts the still-open deal in no-next-action. - [ ] The fixture reports USD 350 and a separate EUR total, never a combined number. - [ ] A private-data authorization check passes using a second identity. - [ ] An off-host restore drill has a date, observed result and recovery time in OPERATIONS.md. - [ ] README names the excluded vendor capabilities and actual provider/hosting costs. ## Launch constraint Do not market omitted Pipedrive capabilities as implemented. The non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
.env.example
# Copy to .env and fill in. Never commit .env; this file documents it. # Required. A new private folder this application creates on first run; never serve it as static files. DATA_DIR=./data/pipedrive # Required · secret. Generate with python -c "import secrets; print(secrets.token_hex(32))" and save only in .env. SECRET_KEY=replace-with-a-random-secret # Required. Use indie for loopback-only personal work. Product mode must refuse to start until owner login and the deployment gates are configured. APP_MODE=indie # Required. The origin used for local forms and links; replace with the chosen HTTPS origin in product mode. SITE_URL=http://127.0.0.1:5000
$ choose a build depth, inspect the files, then open the complete pack in your agent
People still pay for Pipedrive because CRM value compounds as the system becomes the shared memory of every customer interaction and embeds itself in the rest of the stack. The recurring cost buys deduplication, permissions, imports, sync, enrichment, email capture, automations, backups, and audit history, not just the visible interface.
xemail sync, automations, marketplace, reporting, mobile apps, and sales workflow polish
xautomatic email and calendar capture
xdata enrichment
xlarge integration ecosystem
xenterprise reporting
share on X ↗"I just replaced Pipedrive ($14/mo) with one prompt"
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Pipedrive pricing
| plan | monthly | annual (per mo) | what you get |
|---|---|---|---|
| lite | — | $14/user | 2,500 leads+deals per paid seat (company cap 300,000), 30 custom fields, 15 reports/user, 0 automations; contacts unlimited |
| growth | — | $39/user | 5,000 leads+deals/seat (company cap 300,000), 100 custom fields, 50 reports/user, 50 automations/company, 5 sequences |
| premium | — | $59/user | 15,000 leads+deals/seat (company cap 300,000), 300 custom fields, 250 reports/user, 150 automations/company, 100 enrichment credits |
| ultimate | — | $79/user | 20,000 leads+deals/seat (company cap 300,000), 500 custom fields, 500 reports/user, 250 automations/company, 500 enrichment credits |
free tierno free tier (14-day free trial; no credit card required)
billingmonthly + annual (annual page says save up to 42%); verified annual USD rates above, monthly USD rates not exposed in retrievable official text
hidden costsCompany-level add-ons are extra: LeadBooster from $32.50/month, Projects $6.67, Campaigns $13.33, Web Visitors $41 and Smart Docs $32.50 on annual billing; some are included only on higher plans. Lead/deal limits scale per seat but stop at a 300,000-company cap.
verified 2026-08-12 · source ↗
Vibecode Pipedrive
Kinda. The core of Pipedrive is buildable in a weekend with the prompt on this page, but there are real gaps: email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish, automatic email and calendar capture. Read the honest list above before committing.
How much does Pipedrive cost?
Pipedrive costs about $14/month (Lite, checked 2026-08-12), which is $168 per year.
What do I lose by replacing Pipedrive?
Honestly: email sync, automations, marketplace, reporting, mobile apps, and sales workflow polish; automatic email and calendar capture; data enrichment; large integration ecosystem; enterprise reporting. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Pipedrive?
Yes: Twenty (A modern pipeline CRM with custom objects, views and mailbox sync; the subscription becomes a Compose file.) Odoo Community (A free CRM buried inside an ERP the size of a small country; excellent if you can ignore the rest.) Krayin CRM (A Laravel sales pipeline with leads, contacts and email; glossy enough, but it still wants a PHP stack.) All 8 curated free alternatives are at vibecodeit.com/pipedrive/alternatives. The prompt is for when you want it exactly your way.