Vibecode ManyChat
track this build5 steps, step by step0%NOT REALLY · don't bother
The flow builder is the visible part and it is not the hard part: keyword triggers, branching, delays and tags are a weekend of CRUD and a state machine. The hard part is that every message goes through Meta, and Meta decides who gets to send it. To reply to arbitrary strangers who DM your Instagram account you need a reviewed app with advanced messaging permissions, a linked Facebook page, business verification, and compliance with the 24 hour window and human agent tag rules. ManyChat has already cleared all of that and maintains it as the APIs churn. A DIY bot works fine for accounts you personally control in dev mode, which is exactly the audience that does not need automation.
the project pack4 files · fastest path to a working personal build
You are building a lean indie version of ManyChat. 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 ===== # ManyChat indie build ## Goal Build the smallest trustworthy replacement for the core ManyChat workflow for one developer or a tiny team. ## Scope A self-hosted webhook server that receives Instagram or Messenger events and runs your keyword-triggered reply flows from a JSON config, storing contacts and state in SQLite. ## 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: - Pre-approved Meta Business Partner status, so your bot only talks to testers until review passes - The visual flow editor that non-engineers can actually edit without touching JSON - Multi-channel parity: WhatsApp, SMS and email in one contact record - Comment-to-DM triggers, story reply triggers, ads-click entry points and other Meta surface coverage - Deliverability guardrails: 24 hour window handling, message tags, broadcast policy compliance baked in If those capabilities are essential, use ManyChat 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 a self-hosted Instagram/Messenger DM autoresponder called "dmflow". Node 20, TypeScript, Fastify, better-sqlite3, no ORM, no frontend framework. Stack decisions are final, do not offer alternatives. What it does: 1. POST /webhook receives Meta Messenger and Instagram messaging webhook events. GET /webhook handles the hub.challenge verification using VERIFY_TOKEN from .env. 2. Verify the X-Hub-Signature-256 header against APP_SECRET and reject anything that fails. 3. Store contacts (platform, psid, first_seen, last_inbound_at, tags) and a messages log in SQLite at ./data/dmflow.db. Create the schema on boot if missing. 4. Load flows from ./flows/*.json. A flow has: id, triggers (array of keyword strings, matched case-insensitively on the inbound text, plus an optional "default" fallback flow), and steps. Step types: send_text, send_buttons (title plus up to 3 postback buttons), wait (seconds), add_tag, set_field, goto (another flow id). 5. Run a small state machine per contact: current flow id, current step index, collected fields. Persist state so a restart resumes correctly. 6. Outbound sends go to the Graph API /me/messages with PAGE_ACCESS_TOKEN. Respect the 24 hour window: if last_inbound_at is older than 24 hours, refuse to send and log the reason instead of retrying forever. 7. Retry failed sends up to 3 times with exponential backoff, then dead-letter the message into a table. 8. Serve a single read-only HTML page at / rendering contacts, their tags, and the last 50 messages. Plain server-rendered HTML, no JS build step. Out of scope: WhatsApp, SMS, email, a visual flow editor, multi-user auth, analytics dashboards, broadcast sending. Secrets in .env only: VERIFY_TOKEN, APP_SECRET, PAGE_ACCESS_TOKEN, PORT. Ship .env.example. No telemetry, no third party services beyond Meta's Graph API. Include two example flows in ./flows: a keyword flow for "price" and a default greeting flow. Write a README that states plainly that until the Meta app passes review for advanced messaging permissions, this will only reply to accounts added as app testers, and that this is a limitation of Meta, not of the code. ## Required capabilities - Meta developer app with a professional Instagram account linked to a Facebook page - App review for advanced messaging permissions if you want to reply to non-testers - Publicly reachable HTTPS endpoint for the webhook (tunnel or small VPS) - Willingness to fix the integration whenever Meta changes the API ## 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 ManyChat. 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 ===== # ManyChat indie build ## Goal Build the smallest trustworthy replacement for the core ManyChat workflow for one developer or a tiny team. ## Scope A self-hosted webhook server that receives Instagram or Messenger events and runs your keyword-triggered reply flows from a JSON config, storing contacts and state in SQLite. ## 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: - Pre-approved Meta Business Partner status, so your bot only talks to testers until review passes - The visual flow editor that non-engineers can actually edit without touching JSON - Multi-channel parity: WhatsApp, SMS and email in one contact record - Comment-to-DM triggers, story reply triggers, ads-click entry points and other Meta surface coverage - Deliverability guardrails: 24 hour window handling, message tags, broadcast policy compliance baked in If those capabilities are essential, use ManyChat 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 a self-hosted Instagram/Messenger DM autoresponder called "dmflow". Node 20, TypeScript, Fastify, better-sqlite3, no ORM, no frontend framework. Stack decisions are final, do not offer alternatives. What it does: 1. POST /webhook receives Meta Messenger and Instagram messaging webhook events. GET /webhook handles the hub.challenge verification using VERIFY_TOKEN from .env. 2. Verify the X-Hub-Signature-256 header against APP_SECRET and reject anything that fails. 3. Store contacts (platform, psid, first_seen, last_inbound_at, tags) and a messages log in SQLite at ./data/dmflow.db. Create the schema on boot if missing. 4. Load flows from ./flows/*.json. A flow has: id, triggers (array of keyword strings, matched case-insensitively on the inbound text, plus an optional "default" fallback flow), and steps. Step types: send_text, send_buttons (title plus up to 3 postback buttons), wait (seconds), add_tag, set_field, goto (another flow id). 5. Run a small state machine per contact: current flow id, current step index, collected fields. Persist state so a restart resumes correctly. 6. Outbound sends go to the Graph API /me/messages with PAGE_ACCESS_TOKEN. Respect the 24 hour window: if last_inbound_at is older than 24 hours, refuse to send and log the reason instead of retrying forever. 7. Retry failed sends up to 3 times with exponential backoff, then dead-letter the message into a table. 8. Serve a single read-only HTML page at / rendering contacts, their tags, and the last 50 messages. Plain server-rendered HTML, no JS build step. Out of scope: WhatsApp, SMS, email, a visual flow editor, multi-user auth, analytics dashboards, broadcast sending. Secrets in .env only: VERIFY_TOKEN, APP_SECRET, PAGE_ACCESS_TOKEN, PORT. Ship .env.example. No telemetry, no third party services beyond Meta's Graph API. Include two example flows in ./flows: a keyword flow for "price" and a default greeting flow. Write a README that states plainly that until the Meta app passes review for advanced messaging permissions, this will only reply to accounts added as app testers, and that this is a limitation of Meta, not of the code. ## Required capabilities - Meta developer app with a professional Instagram account linked to a Facebook page - App review for advanced messaging permissions if you want to reply to non-testers - Publicly reachable HTTPS endpoint for the webhook (tunnel or small VPS) - Willingness to fix the integration whenever Meta changes the API ## 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 ManyChat. 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 ===== # ManyChat product brief ## Problem The flow builder is the visible part and it is not the hard part: keyword triggers, branching, delays and tags are a weekend of CRUD and a state machine. The hard part is that every message goes through Meta, and Meta decides who gets to send it. To reply to arbitrary strangers who DM your Instagram account you need a reviewed app with advanced messaging permissions, a linked Facebook page, business verification, and compliance with the 24 hour window and human agent tag rules. ManyChat has already cleared all of that and maintains it as the APIs churn. A DIY bot works fine for accounts you personally control in dev mode, which is exactly the audience that does not need automation. ## Product outcome A self-hosted webhook server that receives Instagram or Messenger events and runs your keyword-triggered reply flows from a JSON config, storing contacts and state in SQLite. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - Meta developer app with a professional Instagram account linked to a Facebook page - App review for advanced messaging permissions if you want to reply to non-testers - Publicly reachable HTTPS endpoint for the webhook (tunnel or small VPS) - Willingness to fix the integration whenever Meta changes the API ## Explicit non-goals for v1 - Pre-approved Meta Business Partner status, so your bot only talks to testers until review passes - The visual flow editor that non-engineers can actually edit without touching JSON - Multi-channel parity: WhatsApp, SMS and email in one contact record - Comment-to-DM triggers, story reply triggers, ads-click entry points and other Meta surface coverage - Deliverability guardrails: 24 hour window handling, message tags, broadcast policy compliance baked in ## 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 a self-hosted Instagram/Messenger DM autoresponder called "dmflow". Node 20, TypeScript, Fastify, better-sqlite3, no ORM, no frontend framework. Stack decisions are final, do not offer alternatives. What it does: 1. POST /webhook receives Meta Messenger and Instagram messaging webhook events. GET /webhook handles the hub.challenge verification using VERIFY_TOKEN from .env. 2. Verify the X-Hub-Signature-256 header against APP_SECRET and reject anything that fails. 3. Store contacts (platform, psid, first_seen, last_inbound_at, tags) and a messages log in SQLite at ./data/dmflow.db. Create the schema on boot if missing. 4. Load flows from ./flows/*.json. A flow has: id, triggers (array of keyword strings, matched case-insensitively on the inbound text, plus an optional "default" fallback flow), and steps. Step types: send_text, send_buttons (title plus up to 3 postback buttons), wait (seconds), add_tag, set_field, goto (another flow id). 5. Run a small state machine per contact: current flow id, current step index, collected fields. Persist state so a restart resumes correctly. 6. Outbound sends go to the Graph API /me/messages with PAGE_ACCESS_TOKEN. Respect the 24 hour window: if last_inbound_at is older than 24 hours, refuse to send and log the reason instead of retrying forever. 7. Retry failed sends up to 3 times with exponential backoff, then dead-letter the message into a table. 8. Serve a single read-only HTML page at / rendering contacts, their tags, and the last 50 messages. Plain server-rendered HTML, no JS build step. Out of scope: WhatsApp, SMS, email, a visual flow editor, multi-user auth, analytics dashboards, broadcast sending. Secrets in .env only: VERIFY_TOKEN, APP_SECRET, PAGE_ACCESS_TOKEN, PORT. Ship .env.example. No telemetry, no third party services beyond Meta's Graph API. Include two example flows in ./flows: a keyword flow for "price" and a default greeting flow. Write a README that states plainly that until the Meta app passes review for advanced messaging permissions, this will only reply to accounts added as app testers, and that this is a limitation of Meta, not of the code. ## 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 ManyChat capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
README.md
# ManyChat indie build ## Goal Build the smallest trustworthy replacement for the core ManyChat workflow for one developer or a tiny team. ## Scope A self-hosted webhook server that receives Instagram or Messenger events and runs your keyword-triggered reply flows from a JSON config, storing contacts and state in SQLite. ## 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: - Pre-approved Meta Business Partner status, so your bot only talks to testers until review passes - The visual flow editor that non-engineers can actually edit without touching JSON - Multi-channel parity: WhatsApp, SMS and email in one contact record - Comment-to-DM triggers, story reply triggers, ads-click entry points and other Meta surface coverage - Deliverability guardrails: 24 hour window handling, message tags, broadcast policy compliance baked in If those capabilities are essential, use ManyChat 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 a self-hosted Instagram/Messenger DM autoresponder called "dmflow". Node 20, TypeScript, Fastify, better-sqlite3, no ORM, no frontend framework. Stack decisions are final, do not offer alternatives. What it does: 1. POST /webhook receives Meta Messenger and Instagram messaging webhook events. GET /webhook handles the hub.challenge verification using VERIFY_TOKEN from .env. 2. Verify the X-Hub-Signature-256 header against APP_SECRET and reject anything that fails. 3. Store contacts (platform, psid, first_seen, last_inbound_at, tags) and a messages log in SQLite at ./data/dmflow.db. Create the schema on boot if missing. 4. Load flows from ./flows/*.json. A flow has: id, triggers (array of keyword strings, matched case-insensitively on the inbound text, plus an optional "default" fallback flow), and steps. Step types: send_text, send_buttons (title plus up to 3 postback buttons), wait (seconds), add_tag, set_field, goto (another flow id). 5. Run a small state machine per contact: current flow id, current step index, collected fields. Persist state so a restart resumes correctly. 6. Outbound sends go to the Graph API /me/messages with PAGE_ACCESS_TOKEN. Respect the 24 hour window: if last_inbound_at is older than 24 hours, refuse to send and log the reason instead of retrying forever. 7. Retry failed sends up to 3 times with exponential backoff, then dead-letter the message into a table. 8. Serve a single read-only HTML page at / rendering contacts, their tags, and the last 50 messages. Plain server-rendered HTML, no JS build step. Out of scope: WhatsApp, SMS, email, a visual flow editor, multi-user auth, analytics dashboards, broadcast sending. Secrets in .env only: VERIFY_TOKEN, APP_SECRET, PAGE_ACCESS_TOKEN, PORT. Ship .env.example. No telemetry, no third party services beyond Meta's Graph API. Include two example flows in ./flows: a keyword flow for "price" and a default greeting flow. Write a README that states plainly that until the Meta app passes review for advanced messaging permissions, this will only reply to accounts added as app testers, and that this is a limitation of Meta, not of the code. ## Required capabilities - Meta developer app with a professional Instagram account linked to a Facebook page - App review for advanced messaging permissions if you want to reply to non-testers - Publicly reachable HTTPS endpoint for the webhook (tunnel or small VPS) - Willingness to fix the integration whenever Meta changes the API ## 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
# ManyChat product brief ## Problem The flow builder is the visible part and it is not the hard part: keyword triggers, branching, delays and tags are a weekend of CRUD and a state machine. The hard part is that every message goes through Meta, and Meta decides who gets to send it. To reply to arbitrary strangers who DM your Instagram account you need a reviewed app with advanced messaging permissions, a linked Facebook page, business verification, and compliance with the 24 hour window and human agent tag rules. ManyChat has already cleared all of that and maintains it as the APIs churn. A DIY bot works fine for accounts you personally control in dev mode, which is exactly the audience that does not need automation. ## Product outcome A self-hosted webhook server that receives Instagram or Messenger events and runs your keyword-triggered reply flows from a JSON config, storing contacts and state in SQLite. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - Meta developer app with a professional Instagram account linked to a Facebook page - App review for advanced messaging permissions if you want to reply to non-testers - Publicly reachable HTTPS endpoint for the webhook (tunnel or small VPS) - Willingness to fix the integration whenever Meta changes the API ## Explicit non-goals for v1 - Pre-approved Meta Business Partner status, so your bot only talks to testers until review passes - The visual flow editor that non-engineers can actually edit without touching JSON - Multi-channel parity: WhatsApp, SMS and email in one contact record - Comment-to-DM triggers, story reply triggers, ads-click entry points and other Meta surface coverage - Deliverability guardrails: 24 hour window handling, message tags, broadcast policy compliance baked in ## 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 a self-hosted Instagram/Messenger DM autoresponder called "dmflow". Node 20, TypeScript, Fastify, better-sqlite3, no ORM, no frontend framework. Stack decisions are final, do not offer alternatives. What it does: 1. POST /webhook receives Meta Messenger and Instagram messaging webhook events. GET /webhook handles the hub.challenge verification using VERIFY_TOKEN from .env. 2. Verify the X-Hub-Signature-256 header against APP_SECRET and reject anything that fails. 3. Store contacts (platform, psid, first_seen, last_inbound_at, tags) and a messages log in SQLite at ./data/dmflow.db. Create the schema on boot if missing. 4. Load flows from ./flows/*.json. A flow has: id, triggers (array of keyword strings, matched case-insensitively on the inbound text, plus an optional "default" fallback flow), and steps. Step types: send_text, send_buttons (title plus up to 3 postback buttons), wait (seconds), add_tag, set_field, goto (another flow id). 5. Run a small state machine per contact: current flow id, current step index, collected fields. Persist state so a restart resumes correctly. 6. Outbound sends go to the Graph API /me/messages with PAGE_ACCESS_TOKEN. Respect the 24 hour window: if last_inbound_at is older than 24 hours, refuse to send and log the reason instead of retrying forever. 7. Retry failed sends up to 3 times with exponential backoff, then dead-letter the message into a table. 8. Serve a single read-only HTML page at / rendering contacts, their tags, and the last 50 messages. Plain server-rendered HTML, no JS build step. Out of scope: WhatsApp, SMS, email, a visual flow editor, multi-user auth, analytics dashboards, broadcast sending. Secrets in .env only: VERIFY_TOKEN, APP_SECRET, PAGE_ACCESS_TOKEN, PORT. Ship .env.example. No telemetry, no third party services beyond Meta's Graph API. Include two example flows in ./flows: a keyword flow for "price" and a default greeting flow. Write a README that states plainly that until the Meta app passes review for advanced messaging permissions, this will only reply to accounts added as app testers, and that this is a limitation of Meta, not of the code. ## 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 ManyChat 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 · this prompt is generated from the build plan · improve it via PR
Because the bottleneck is access, not code. Anyone selling through Instagram DMs needs messages that actually reach strangers who commented on a post, and that requires permissions Meta grants to reviewed apps and revokes when policy shifts. ManyChat absorbs that risk, keeps the connectors alive across API versions, and hands a marketing person a canvas they can edit at 11pm without a deploy. Fifteen dollars a month against a broken funnel is not a hard call.
xPre-approved Meta Business Partner status, so your bot only talks to testers until review passes
xThe visual flow editor that non-engineers can actually edit without touching JSON
xMulti-channel parity: WhatsApp, SMS and email in one contact record
xComment-to-DM triggers, story reply triggers, ads-click entry points and other Meta surface coverage
xDeliverability guardrails: 24 hour window handling, message tags, broadcast policy compliance baked in
Nothing worth pointing at. That's why the prompt exists.
share on X ↗"I just replaced ManyChat ($39/mo) with one prompt"
Vibecode ManyChat
Not really. ManyChat's value is not the code: The moat is Meta platform access plus the standing compliance work to keep it. See the honest breakdown above.
How much does ManyChat cost?
ManyChat costs about $39/month (Pro, checked 2026-08-18), which is $468 per year.
What do I lose by replacing ManyChat?
Honestly: Pre-approved Meta Business Partner status, so your bot only talks to testers until review passes; The visual flow editor that non-engineers can actually edit without touching JSON; Multi-channel parity: WhatsApp, SMS and email in one contact record; Comment-to-DM triggers, story reply triggers, ads-click entry points and other Meta surface coverage; Deliverability guardrails: 24 hour window handling, message tags, broadcast policy compliance baked in. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to ManyChat?
No mature open-source alternative worth pointing at, which is exactly why the one-shot prompt on this page exists.