Vibecode Outstand

You are building a lean indie version of Outstand.

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 =====
# Outstand indie build

## Goal

Build the smallest trustworthy replacement for the core Outstand workflow for one developer or a tiny team.

## Scope

Run a small self-hosted service that takes a post plus target accounts over HTTP, queues it, publishes on schedule through one adapter per network, and records per-account delivery status.

## 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 platform apps for Instagram, TikTok, YouTube and LinkedIn
- eleven maintained integrations, kept alive as platforms change
- automatic token refresh and rate-limit queueing
- per-network media transcoding from a single upload
- cross-platform analytics in one shape
- the MCP server that hands all of it to an AI agent

If those capabilities are essential, use postiz-app 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 self-hosted unified posting API to replace Outstand. Requirements:

- Node + Fastify + better-sqlite3, one headless service on localhost:8080.
  No web UI: my own apps are the only consumer, every key in .env.
- One normalized post shape in zod (text, media, targets, scheduledAt,
  idempotencyKey) and one adapter per network mapping it onto that
  platform's payload. Adapters export capabilities, publish, and metrics;
  nothing platform-specific leaks into the core.
- A capability table per adapter (character limit, media count, mime types,
  aspect ratios, max video seconds). POST /posts returns 422 naming which
  target rejected what, before a single network call goes out.
- Ship the three networks that need no app review: Bluesky (@atproto/api),
  Mastodon, Telegram. Adding a fourth must mean writing one adapter file
  and touching nothing else.
- A token-bucket limiter per network seeded with their published limits so
  calls queue instead of returning 429. POST /posts answers 202 with a job
  id and a worker drains the queue.
- Idempotency: replaying a POST with the same idempotencyKey returns the
  original job instead of posting twice, and every target gets its own
  delivery row so partial success is readable.
- GET /posts/:id/analytics folds each platform's metrics into one shape
  (impressions, likes, comments, shares) with null where a network does not
  report a field. Never invent a number to fill a gap.
- An MCP server over stdio exposing create_post, list_accounts, and
  get_analytics so Claude Code posts through it, plus an OpenAPI spec
  generated from the zod schemas at /openapi.json.
- Out of scope: Instagram, TikTok, YouTube, LinkedIn, Pinterest. Each needs
  my own developer app approved by the platform first, a review queue and
  not code. Say that in the README next to the three token setups.

## Required capabilities

- your own developer app per social network
- paid X API tier for posting to X
- always-on box for the scheduler
- media storage

## 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 Outstand.

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 =====
# Outstand indie build

## Goal

Build the smallest trustworthy replacement for the core Outstand workflow for one developer or a tiny team.

## Scope

Run a small self-hosted service that takes a post plus target accounts over HTTP, queues it, publishes on schedule through one adapter per network, and records per-account delivery status.

## 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 platform apps for Instagram, TikTok, YouTube and LinkedIn
- eleven maintained integrations, kept alive as platforms change
- automatic token refresh and rate-limit queueing
- per-network media transcoding from a single upload
- cross-platform analytics in one shape
- the MCP server that hands all of it to an AI agent

If those capabilities are essential, use postiz-app 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 self-hosted unified posting API to replace Outstand. Requirements:

- Node + Fastify + better-sqlite3, one headless service on localhost:8080.
  No web UI: my own apps are the only consumer, every key in .env.
- One normalized post shape in zod (text, media, targets, scheduledAt,
  idempotencyKey) and one adapter per network mapping it onto that
  platform's payload. Adapters export capabilities, publish, and metrics;
  nothing platform-specific leaks into the core.
- A capability table per adapter (character limit, media count, mime types,
  aspect ratios, max video seconds). POST /posts returns 422 naming which
  target rejected what, before a single network call goes out.
- Ship the three networks that need no app review: Bluesky (@atproto/api),
  Mastodon, Telegram. Adding a fourth must mean writing one adapter file
  and touching nothing else.
- A token-bucket limiter per network seeded with their published limits so
  calls queue instead of returning 429. POST /posts answers 202 with a job
  id and a worker drains the queue.
- Idempotency: replaying a POST with the same idempotencyKey returns the
  original job instead of posting twice, and every target gets its own
  delivery row so partial success is readable.
- GET /posts/:id/analytics folds each platform's metrics into one shape
  (impressions, likes, comments, shares) with null where a network does not
  report a field. Never invent a number to fill a gap.
- An MCP server over stdio exposing create_post, list_accounts, and
  get_analytics so Claude Code posts through it, plus an OpenAPI spec
  generated from the zod schemas at /openapi.json.
- Out of scope: Instagram, TikTok, YouTube, LinkedIn, Pinterest. Each needs
  my own developer app approved by the platform first, a review queue and
  not code. Say that in the README next to the three token setups.

## Required capabilities

- your own developer app per social network
- paid X API tier for posting to X
- always-on box for the scheduler
- media storage

## 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 Outstand.

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 =====
# Outstand product brief

## Problem

Writing your own posting service is a weekend build, and for the networks with open APIs (Bluesky, Mastodon, Telegram) it genuinely is: a queue, a cron tick, one adapter per network, done. The wall is not code. Instagram, TikTok, YouTube, LinkedIn, and Pinterest each require your own developer app and a platform review before they will accept a single post, X meters writes on a paid tier, and then eleven integrations keep changing under you: token refresh, media specs, rate-limit budgets, deprecated endpoints. You can build the API. You cannot one-shot permission to use it.

## Product outcome

Run a small self-hosted service that takes a post plus target accounts over HTTP, queues it, publishes on schedule through one adapter per network, and records per-account delivery status.

## Target user

A serious builder who needs a maintainable product foundation rather than a one-off demo.

## Required capabilities

- your own developer app per social network
- paid X API tier for posting to X
- always-on box for the scheduler
- media storage

## Explicit non-goals for v1

- pre-approved platform apps for Instagram, TikTok, YouTube and LinkedIn
- eleven maintained integrations, kept alive as platforms change
- automatic token refresh and rate-limit queueing
- per-network media transcoding from a single upload
- cross-platform analytics in one shape
- the MCP server that hands all of it to an AI agent

## 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 self-hosted unified posting API to replace Outstand. Requirements:

- Node + Fastify + better-sqlite3, one headless service on localhost:8080.
  No web UI: my own apps are the only consumer, every key in .env.
- One normalized post shape in zod (text, media, targets, scheduledAt,
  idempotencyKey) and one adapter per network mapping it onto that
  platform's payload. Adapters export capabilities, publish, and metrics;
  nothing platform-specific leaks into the core.
- A capability table per adapter (character limit, media count, mime types,
  aspect ratios, max video seconds). POST /posts returns 422 naming which
  target rejected what, before a single network call goes out.
- Ship the three networks that need no app review: Bluesky (@atproto/api),
  Mastodon, Telegram. Adding a fourth must mean writing one adapter file
  and touching nothing else.
- A token-bucket limiter per network seeded with their published limits so
  calls queue instead of returning 429. POST /posts answers 202 with a job
  id and a worker drains the queue.
- Idempotency: replaying a POST with the same idempotencyKey returns the
  original job instead of posting twice, and every target gets its own
  delivery row so partial success is readable.
- GET /posts/:id/analytics folds each platform's metrics into one shape
  (impressions, likes, comments, shares) with null where a network does not
  report a field. Never invent a number to fill a gap.
- An MCP server over stdio exposing create_post, list_accounts, and
  get_analytics so Claude Code posts through it, plus an OpenAPI spec
  generated from the zod schemas at /openapi.json.
- Out of scope: Instagram, TikTok, YouTube, LinkedIn, Pinterest. Each needs
  my own developer app approved by the platform first, a review queue and
  not code. Say that in the README next to the three token setups.

## 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 Outstand capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.

# Outstand indie build

## Goal

Build the smallest trustworthy replacement for the core Outstand workflow for one developer or a tiny team.

## Scope

Run a small self-hosted service that takes a post plus target accounts over HTTP, queues it, publishes on schedule through one adapter per network, and records per-account delivery status.

## 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 platform apps for Instagram, TikTok, YouTube and LinkedIn
- eleven maintained integrations, kept alive as platforms change
- automatic token refresh and rate-limit queueing
- per-network media transcoding from a single upload
- cross-platform analytics in one shape
- the MCP server that hands all of it to an AI agent

If those capabilities are essential, use postiz-app instead of pretending the gap is solved.

# 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

## Original build brief

Build me a self-hosted unified posting API to replace Outstand. Requirements:

- Node + Fastify + better-sqlite3, one headless service on localhost:8080.
  No web UI: my own apps are the only consumer, every key in .env.
- One normalized post shape in zod (text, media, targets, scheduledAt,
  idempotencyKey) and one adapter per network mapping it onto that
  platform's payload. Adapters export capabilities, publish, and metrics;
  nothing platform-specific leaks into the core.
- A capability table per adapter (character limit, media count, mime types,
  aspect ratios, max video seconds). POST /posts returns 422 naming which
  target rejected what, before a single network call goes out.
- Ship the three networks that need no app review: Bluesky (@atproto/api),
  Mastodon, Telegram. Adding a fourth must mean writing one adapter file
  and touching nothing else.
- A token-bucket limiter per network seeded with their published limits so
  calls queue instead of returning 429. POST /posts answers 202 with a job
  id and a worker drains the queue.
- Idempotency: replaying a POST with the same idempotencyKey returns the
  original job instead of posting twice, and every target gets its own
  delivery row so partial success is readable.
- GET /posts/:id/analytics folds each platform's metrics into one shape
  (impressions, likes, comments, shares) with null where a network does not
  report a field. Never invent a number to fill a gap.
- An MCP server over stdio exposing create_post, list_accounts, and
  get_analytics so Claude Code posts through it, plus an OpenAPI spec
  generated from the zod schemas at /openapi.json.
- Out of scope: Instagram, TikTok, YouTube, LinkedIn, Pinterest. Each needs
  my own developer app approved by the platform first, a review queue and
  not code. Say that in the README next to the three token setups.

## Required capabilities

- your own developer app per social network
- paid X API tier for posting to X
- always-on box for the scheduler
- media storage

## 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.

# 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.

# Outstand product brief

## Problem

Writing your own posting service is a weekend build, and for the networks with open APIs (Bluesky, Mastodon, Telegram) it genuinely is: a queue, a cron tick, one adapter per network, done. The wall is not code. Instagram, TikTok, YouTube, LinkedIn, and Pinterest each require your own developer app and a platform review before they will accept a single post, X meters writes on a paid tier, and then eleven integrations keep changing under you: token refresh, media specs, rate-limit budgets, deprecated endpoints. You can build the API. You cannot one-shot permission to use it.

## Product outcome

Run a small self-hosted service that takes a post plus target accounts over HTTP, queues it, publishes on schedule through one adapter per network, and records per-account delivery status.

## Target user

A serious builder who needs a maintainable product foundation rather than a one-off demo.

## Required capabilities

- your own developer app per social network
- paid X API tier for posting to X
- always-on box for the scheduler
- media storage

## Explicit non-goals for v1

- pre-approved platform apps for Instagram, TikTok, YouTube and LinkedIn
- eleven maintained integrations, kept alive as platforms change
- automatic token refresh and rate-limit queueing
- per-network media transcoding from a single upload
- cross-platform analytics in one shape
- the MCP server that hands all of it to an AI agent

## 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

## Starting brief

Build me a self-hosted unified posting API to replace Outstand. Requirements:

- Node + Fastify + better-sqlite3, one headless service on localhost:8080.
  No web UI: my own apps are the only consumer, every key in .env.
- One normalized post shape in zod (text, media, targets, scheduledAt,
  idempotencyKey) and one adapter per network mapping it onto that
  platform's payload. Adapters export capabilities, publish, and metrics;
  nothing platform-specific leaks into the core.
- A capability table per adapter (character limit, media count, mime types,
  aspect ratios, max video seconds). POST /posts returns 422 naming which
  target rejected what, before a single network call goes out.
- Ship the three networks that need no app review: Bluesky (@atproto/api),
  Mastodon, Telegram. Adding a fourth must mean writing one adapter file
  and touching nothing else.
- A token-bucket limiter per network seeded with their published limits so
  calls queue instead of returning 429. POST /posts answers 202 with a job
  id and a worker drains the queue.
- Idempotency: replaying a POST with the same idempotencyKey returns the
  original job instead of posting twice, and every target gets its own
  delivery row so partial success is readable.
- GET /posts/:id/analytics folds each platform's metrics into one shape
  (impressions, likes, comments, shares) with null where a network does not
  report a field. Never invent a number to fill a gap.
- An MCP server over stdio exposing create_post, list_accounts, and
  get_analytics so Claude Code posts through it, plus an OpenAPI spec
  generated from the zod schemas at /openapi.json.
- Out of scope: Instagram, TikTok, YouTube, LinkedIn, Pinterest. Each needs
  my own developer app approved by the platform first, a review queue and
  not code. Say that in the README next to the three token setups.

## 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.

# 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.

# 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

## 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 Outstand 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