Vibecode PromptDrive
track this build5 steps, step by step0%YES · one-shottable
The core loop, save a prompt, file it in a folder, tag it, find it, fill in variables, copy it into a chat, is a small CRUD app around one SQLite table and ships in one sitting. What the subscription actually sells is the multiplayer part: shared folders with permissions, comments that let a team iterate on a prompt, and a Chrome extension that surfaces the library inside ChatGPT, Claude, and Gemini.
the project pack4 files · fastest path to a working personal build
You are building a lean indie version of PromptDrive.
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 =====
# PromptDrive indie build
## Goal
Build the smallest trustworthy replacement for the core PromptDrive workflow for one developer or a tiny team.
## Scope
Save prompts with folders and tags in SQLite, search them as you type, fill {{variables}} in a generated form, and copy the result into any chat AI.
## Quick start
1. Install the documented dependencies.
2. Copy `.env.example` to `.env`.
3. Run the development command chosen during implementation.
4. Complete the acceptance checks in `BUILD_PLAN.md`.
## Honest limits
This build deliberately does not replace:
- team sharing, comments, and permissions
- the Chrome extension inside ChatGPT, Claude, and Gemini
- running prompts against models from the same workspace with your own API keys
- public share links with unique URLs
- someone else's servers & support
If those capabilities are essential, use Langfuse instead of pretending the gap is solved.
===== AGENTS.md =====
# Agent instructions
- Optimize for a working, understandable weekend build.
- Prefer the fewest moving parts that satisfy the brief.
- Do not invent cryptography, security guarantees, APIs, or compliance claims.
- Keep secrets out of source control and logs.
- Add focused tests for destructive, security-sensitive, and data-loss paths.
- Run the project checks before declaring the build complete.
- Record any deliberate shortcut in the README under "Tradeoffs".
===== BUILD_PLAN.md =====
# Build plan
## Original build brief
Build me a local prompt library to replace PromptDrive. Requirements:
- A single-process Node app (Express + better-sqlite3, vanilla HTML/CSS/JS, no build
step) serving a web UI on localhost:4321.
- Prompts have a title, body, notes, a folder, and tags. Store everything in one
SQLite file next to the app; create the schema on first run.
- Full-text search across title, body, and tags with SQLite FTS5, filtering live as
I type.
- Support {{variable}} placeholders in prompt bodies: opening a prompt renders one
input per distinct placeholder and shows the filled prompt update live.
- One-click copy of the filled prompt with navigator.clipboard and a brief copied
confirmation.
- Import and export the whole library as one JSON file from the UI; also export any
folder as Markdown, one file per prompt.
- Keyboard-first: / focuses search, arrow keys move through results, Enter opens,
c copies.
- No accounts, no cloud, no telemetry, no API calls: this is a filing cabinet, not a
chat client. Deliberately out: team sharing, comments, the browser extension, and
running prompts against models.
- Include a README with install and run steps, backup advice (copy the .sqlite
file), and a seed script that loads five example prompts.
## Required capabilities
- Node.js 20+
- a browser
## Delivery order
1. Scaffold the smallest runnable application and document its commands.
2. Implement the primary data model and core workflow.
3. Add validation, safe failure states, and persistence.
4. Cover the critical path with automated tests.
5. Exercise a clean install from the README and fix every missing step.
## Done when
- A new user can go from clone to first successful workflow using only the README.
- The core workflow works without paid infrastructure unless the brief requires it.
- Tests cover the highest-risk behavior.
- Known limitations are explicit rather than hidden.
===== .env.example =====
# Copy to .env and document every variable when it is introduced.
# Never put real credentials in this file.
APP_ENV=development
# Add only values required by the selected implementation.You are building a lean indie version of PromptDrive.
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 =====
# PromptDrive indie build
## Goal
Build the smallest trustworthy replacement for the core PromptDrive workflow for one developer or a tiny team.
## Scope
Save prompts with folders and tags in SQLite, search them as you type, fill {{variables}} in a generated form, and copy the result into any chat AI.
## Quick start
1. Install the documented dependencies.
2. Copy `.env.example` to `.env`.
3. Run the development command chosen during implementation.
4. Complete the acceptance checks in `BUILD_PLAN.md`.
## Honest limits
This build deliberately does not replace:
- team sharing, comments, and permissions
- the Chrome extension inside ChatGPT, Claude, and Gemini
- running prompts against models from the same workspace with your own API keys
- public share links with unique URLs
- someone else's servers & support
If those capabilities are essential, use Langfuse instead of pretending the gap is solved.
===== AGENTS.md =====
# Agent instructions
- Optimize for a working, understandable weekend build.
- Prefer the fewest moving parts that satisfy the brief.
- Do not invent cryptography, security guarantees, APIs, or compliance claims.
- Keep secrets out of source control and logs.
- Add focused tests for destructive, security-sensitive, and data-loss paths.
- Run the project checks before declaring the build complete.
- Record any deliberate shortcut in the README under "Tradeoffs".
===== BUILD_PLAN.md =====
# Build plan
## Original build brief
Build me a local prompt library to replace PromptDrive. Requirements:
- A single-process Node app (Express + better-sqlite3, vanilla HTML/CSS/JS, no build
step) serving a web UI on localhost:4321.
- Prompts have a title, body, notes, a folder, and tags. Store everything in one
SQLite file next to the app; create the schema on first run.
- Full-text search across title, body, and tags with SQLite FTS5, filtering live as
I type.
- Support {{variable}} placeholders in prompt bodies: opening a prompt renders one
input per distinct placeholder and shows the filled prompt update live.
- One-click copy of the filled prompt with navigator.clipboard and a brief copied
confirmation.
- Import and export the whole library as one JSON file from the UI; also export any
folder as Markdown, one file per prompt.
- Keyboard-first: / focuses search, arrow keys move through results, Enter opens,
c copies.
- No accounts, no cloud, no telemetry, no API calls: this is a filing cabinet, not a
chat client. Deliberately out: team sharing, comments, the browser extension, and
running prompts against models.
- Include a README with install and run steps, backup advice (copy the .sqlite
file), and a seed script that loads five example prompts.
## Required capabilities
- Node.js 20+
- a browser
## Delivery order
1. Scaffold the smallest runnable application and document its commands.
2. Implement the primary data model and core workflow.
3. Add validation, safe failure states, and persistence.
4. Cover the critical path with automated tests.
5. Exercise a clean install from the README and fix every missing step.
## Done when
- A new user can go from clone to first successful workflow using only the README.
- The core workflow works without paid infrastructure unless the brief requires it.
- Tests cover the highest-risk behavior.
- Known limitations are explicit rather than hidden.
===== .env.example =====
# Copy to .env and document every variable when it is introduced.
# Never put real credentials in this file.
APP_ENV=development
# Add only values required by the selected implementation.You are building a production product version of PromptDrive.
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 =====
# PromptDrive product brief
## Problem
The core loop, save a prompt, file it in a folder, tag it, find it, fill in variables, copy it into a chat, is a small CRUD app around one SQLite table and ships in one sitting. What the subscription actually sells is the multiplayer part: shared folders with permissions, comments that let a team iterate on a prompt, and a Chrome extension that surfaces the library inside ChatGPT, Claude, and Gemini.
## Product outcome
Save prompts with folders and tags in SQLite, search them as you type, fill {{variables}} in a generated form, and copy the result into any chat AI.
## Target user
A serious builder who needs a maintainable product foundation rather than a one-off demo.
## Required capabilities
- Node.js 20+
- a browser
## Explicit non-goals for v1
- team sharing, comments, and permissions
- the Chrome extension inside ChatGPT, Claude, and Gemini
- running prompts against models from the same workspace with your own API keys
- public share links with unique URLs
- someone else's servers & support
## Success criteria
- The primary workflow is measurable end to end.
- Setup is reproducible in a clean environment.
- Failure, recovery, and support paths are documented.
- Product claims match what the implementation actually guarantees.
===== ARCHITECTURE.md =====
# Architecture
## Starting brief
Build me a local prompt library to replace PromptDrive. Requirements:
- A single-process Node app (Express + better-sqlite3, vanilla HTML/CSS/JS, no build
step) serving a web UI on localhost:4321.
- Prompts have a title, body, notes, a folder, and tags. Store everything in one
SQLite file next to the app; create the schema on first run.
- Full-text search across title, body, and tags with SQLite FTS5, filtering live as
I type.
- Support {{variable}} placeholders in prompt bodies: opening a prompt renders one
input per distinct placeholder and shows the filled prompt update live.
- One-click copy of the filled prompt with navigator.clipboard and a brief copied
confirmation.
- Import and export the whole library as one JSON file from the UI; also export any
folder as Markdown, one file per prompt.
- Keyboard-first: / focuses search, arrow keys move through results, Enter opens,
c copies.
- No accounts, no cloud, no telemetry, no API calls: this is a filing cabinet, not a
chat client. Deliberately out: team sharing, comments, the browser extension, and
running prompts against models.
- Include a README with install and run steps, backup advice (copy the .sqlite
file), and a seed script that loads five example prompts.
## Boundaries
Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors.
## Production baseline
- Configuration: validated at startup with safe local defaults where possible.
- Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives.
- Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions.
- Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts.
- Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists.
- Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test.
## Decision records
For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it.
===== AGENTS.md =====
# Agent instructions
- Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code.
- Implement milestone by milestone; keep each change reviewable and leave the application runnable.
- 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 test pass.
- Use provider interfaces for external services and deterministic fakes in tests.
- Add migrations and rollback or recovery notes for persistent data changes.
- Log useful operational context without credentials, tokens, passwords, or personal data.
- Update documentation and run all checks before completing a milestone.
===== MILESTONES.md =====
# Delivery milestones
## M0 — Decisions and scaffold
- Confirm the runtime, persistence model, threat boundaries, and deployment target.
- Create a reproducible local environment and continuous checks.
## M1 — Core workflow
- Implement the smallest end-to-end product path with validation and tests.
- Keep integrations behind interfaces.
## M2 — Trust layer
- Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards.
- Test abuse cases and destructive operations.
## M3 — Operability
- Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration.
## M4 — Release gate
- Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise.
- Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations.
===== OPERATIONS.md =====
# Operations
## Before release
- Validate configuration and secrets at startup.
- Define backup, restore, and rollback procedures and test them.
- Document logs, error tracking, health signals, and alert ownership.
- Set dependency update and vulnerability review expectations.
## Incident checklist
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 source when needed.
5. Document the root cause, remediation, and regression test.
## Launch constraint
Do not market omitted PromptDrive capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.README.md
# PromptDrive indie build
## Goal
Build the smallest trustworthy replacement for the core PromptDrive workflow for one developer or a tiny team.
## Scope
Save prompts with folders and tags in SQLite, search them as you type, fill {{variables}} in a generated form, and copy the result into any chat AI.
## Quick start
1. Install the documented dependencies.
2. Copy `.env.example` to `.env`.
3. Run the development command chosen during implementation.
4. Complete the acceptance checks in `BUILD_PLAN.md`.
## Honest limits
This build deliberately does not replace:
- team sharing, comments, and permissions
- the Chrome extension inside ChatGPT, Claude, and Gemini
- running prompts against models from the same workspace with your own API keys
- public share links with unique URLs
- someone else's servers & support
If those capabilities are essential, use Langfuse instead of pretending the gap is solved.AGENTS.md
# Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs".
BUILD_PLAN.md
# Build plan
## Original build brief
Build me a local prompt library to replace PromptDrive. Requirements:
- A single-process Node app (Express + better-sqlite3, vanilla HTML/CSS/JS, no build
step) serving a web UI on localhost:4321.
- Prompts have a title, body, notes, a folder, and tags. Store everything in one
SQLite file next to the app; create the schema on first run.
- Full-text search across title, body, and tags with SQLite FTS5, filtering live as
I type.
- Support {{variable}} placeholders in prompt bodies: opening a prompt renders one
input per distinct placeholder and shows the filled prompt update live.
- One-click copy of the filled prompt with navigator.clipboard and a brief copied
confirmation.
- Import and export the whole library as one JSON file from the UI; also export any
folder as Markdown, one file per prompt.
- Keyboard-first: / focuses search, arrow keys move through results, Enter opens,
c copies.
- No accounts, no cloud, no telemetry, no API calls: this is a filing cabinet, not a
chat client. Deliberately out: team sharing, comments, the browser extension, and
running prompts against models.
- Include a README with install and run steps, backup advice (copy the .sqlite
file), and a seed script that loads five example prompts.
## Required capabilities
- Node.js 20+
- a browser
## Delivery order
1. Scaffold the smallest runnable application and document its commands.
2. Implement the primary data model and core workflow.
3. Add validation, safe failure states, and persistence.
4. Cover the critical path with automated tests.
5. Exercise a clean install from the README and fix every missing step.
## Done when
- A new user can go from clone to first successful workflow using only the README.
- The core workflow works without paid infrastructure unless the brief requires it.
- Tests cover the highest-risk behavior.
- Known limitations are explicit rather than hidden..env.example
# Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
PRODUCT.md
# PromptDrive product brief
## Problem
The core loop, save a prompt, file it in a folder, tag it, find it, fill in variables, copy it into a chat, is a small CRUD app around one SQLite table and ships in one sitting. What the subscription actually sells is the multiplayer part: shared folders with permissions, comments that let a team iterate on a prompt, and a Chrome extension that surfaces the library inside ChatGPT, Claude, and Gemini.
## Product outcome
Save prompts with folders and tags in SQLite, search them as you type, fill {{variables}} in a generated form, and copy the result into any chat AI.
## Target user
A serious builder who needs a maintainable product foundation rather than a one-off demo.
## Required capabilities
- Node.js 20+
- a browser
## Explicit non-goals for v1
- team sharing, comments, and permissions
- the Chrome extension inside ChatGPT, Claude, and Gemini
- running prompts against models from the same workspace with your own API keys
- public share links with unique URLs
- someone else's servers & support
## Success criteria
- The primary workflow is measurable end to end.
- Setup is reproducible in a clean environment.
- Failure, recovery, and support paths are documented.
- Product claims match what the implementation actually guarantees.ARCHITECTURE.md
# Architecture
## Starting brief
Build me a local prompt library to replace PromptDrive. Requirements:
- A single-process Node app (Express + better-sqlite3, vanilla HTML/CSS/JS, no build
step) serving a web UI on localhost:4321.
- Prompts have a title, body, notes, a folder, and tags. Store everything in one
SQLite file next to the app; create the schema on first run.
- Full-text search across title, body, and tags with SQLite FTS5, filtering live as
I type.
- Support {{variable}} placeholders in prompt bodies: opening a prompt renders one
input per distinct placeholder and shows the filled prompt update live.
- One-click copy of the filled prompt with navigator.clipboard and a brief copied
confirmation.
- Import and export the whole library as one JSON file from the UI; also export any
folder as Markdown, one file per prompt.
- Keyboard-first: / focuses search, arrow keys move through results, Enter opens,
c copies.
- No accounts, no cloud, no telemetry, no API calls: this is a filing cabinet, not a
chat client. Deliberately out: team sharing, comments, the browser extension, and
running prompts against models.
- Include a README with install and run steps, backup advice (copy the .sqlite
file), and a seed script that loads five example prompts.
## Boundaries
Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors.
## Production baseline
- Configuration: validated at startup with safe local defaults where possible.
- Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives.
- Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions.
- Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts.
- Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists.
- Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test.
## Decision records
For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it.AGENTS.md
# Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - 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 test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone.
MILESTONES.md
# Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations.
OPERATIONS.md
# Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 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 source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted PromptDrive capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
$ choose a build depth, inspect the files, then open the complete pack in your agent
Teams pay for the shared workspace: private folders someone else maintains, comments that turn a prompt into a living document, permissions, and an extension that follows the team into whichever chat AI they use. A local library covers one person fine; the per-seat fee is really about keeping five people on the same page.
xteam sharing, comments, and permissions
xthe Chrome extension inside ChatGPT, Claude, and Gemini
xrunning prompts against models from the same workspace with your own API keys
xpublic share links with unique URLs
xsomeone else's servers & support
share on X ↗"I just replaced PromptDrive ($5/mo) with one prompt"
Don't feel like building it? These folks already made it free.
LangfuseAn open source LLM engineering platform whose prompt management gives a team versioned, shared prompts, if you are happy running the whole stack for that one feature.open source↗no votes, no pay-to-list · just what's real
PromptDrive pricing
team$5/mo · monthly per user · $60/yr
free tierThe free Personal plan includes unlimited prompts, public sharing links, and the Chrome extension.
verified 2026-08-10 · source ↗
Is PromptDrive free?
The free Personal plan includes unlimited prompts, public sharing links, and the Chrome extension. Paid is Team at $5/mo (checked 2026-08-10).
Vibecode PromptDrive
Yes. A competent AI coding agent (Claude Code, Codex, Cursor) can build a usable personal PromptDrive replacement in one session with the prompt on this page. It runs on your own machine or server with no subscription.
How much does PromptDrive cost?
PromptDrive costs about $5/month (Team, checked 2026-08-10), which is $60 per year. That's what you save by replacing it with one prompt.
What do I lose by replacing PromptDrive?
Honestly: team sharing, comments, and permissions; the Chrome extension inside ChatGPT, Claude, and Gemini; running prompts against models from the same workspace with your own API keys; public share links with unique URLs; someone else's servers & support. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to PromptDrive?
Yes: Langfuse (An open source LLM engineering platform whose prompt management gives a team versioned, shared prompts, if you are happy running the whole stack for that one feature.) The prompt is for when you want it exactly your way.