Vibecode Debriefing

You are building a lean indie version of Debriefing.

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 =====
# Debriefing indie build

## Goal

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

## Scope

Snapshot each competitor's key pages on a schedule, diff against the last version, and have a model summarise the meaningful changes into a digest.

## 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:
- noise filtering, which is the actual product: most diffs are rotated testimonials and changed asset hashes, not competitive moves
- horizon watch, meaning the substitutes and new entrants you did not think to add to the list
- the non-page signals stitched into the same brief: hiring, funding, traffic and LinkedIn movement
- the analytical step from what changed to why it matters to what to do next
- an archive going back far enough that a change reads as a trend rather than an event

If those capabilities are essential, use changedetection.io 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 competitor watch that emails me a weekly brief, to replace Debriefing. Requirements:

- Node 22, TypeScript, SQLite via better-sqlite3, Playwright for fetching, node-cron for
  the schedule. CLI only. No accounts, no telemetry, keys in .env.
- competitors.json lists each rival: name, and the URLs that matter (homepage, pricing,
  changelog, careers). Ship it seeded with 3 competitors and 4 URLs each.
- `watch snapshot` fetches every URL with Playwright, strips scripts, styles, nav and
  footer, converts the main content to plain text, and stores it with a SHA-256 hash and
  a timestamp. Skip storage entirely when the hash is unchanged.
- Diff each new snapshot against the previous one as unified text diff. Discard diffs
  under 40 changed characters, and drop lines matching an editable noise.json of regexes
  (dates, cache-busting hashes, view counts, testimonial rotations).
- `watch brief` sends the surviving diffs for the period to Claude or GPT in one call
  and asks for, per competitor: what changed, why it matters, and one suggested response.
  Require a citation back to the exact URL for every claim, and drop any bullet without
  one.
- Render the brief to Markdown in ~/CompetitorBriefs/YYYY-MM-DD.md and send it via SMTP
  from .env. The file is the source of truth, email is just delivery.
- Keep every snapshot and every brief. `watch history <competitor>` prints that rival's
  changes over time, which is the only way a single diff becomes a trend.
- Out of scope: hiring feeds, funding data, traffic estimates, dashboards and any login
  wall. Public pages only, respect robots.txt, one request per URL per run.
- README: setup, a cron line for the weekly run, the per-brief token cost, and a warning
  that month one is mostly tuning noise.json.

## Required capabilities

- an OpenAI or Anthropic API key
- a scheduler and somewhere to keep page snapshots
- a headless browser for pages that render client-side
- SMTP or a Slack webhook for delivery
- patience for the first month of false positives

## 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 Debriefing.

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 =====
# Debriefing indie build

## Goal

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

## Scope

Snapshot each competitor's key pages on a schedule, diff against the last version, and have a model summarise the meaningful changes into a digest.

## 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:
- noise filtering, which is the actual product: most diffs are rotated testimonials and changed asset hashes, not competitive moves
- horizon watch, meaning the substitutes and new entrants you did not think to add to the list
- the non-page signals stitched into the same brief: hiring, funding, traffic and LinkedIn movement
- the analytical step from what changed to why it matters to what to do next
- an archive going back far enough that a change reads as a trend rather than an event

If those capabilities are essential, use changedetection.io 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 competitor watch that emails me a weekly brief, to replace Debriefing. Requirements:

- Node 22, TypeScript, SQLite via better-sqlite3, Playwright for fetching, node-cron for
  the schedule. CLI only. No accounts, no telemetry, keys in .env.
- competitors.json lists each rival: name, and the URLs that matter (homepage, pricing,
  changelog, careers). Ship it seeded with 3 competitors and 4 URLs each.
- `watch snapshot` fetches every URL with Playwright, strips scripts, styles, nav and
  footer, converts the main content to plain text, and stores it with a SHA-256 hash and
  a timestamp. Skip storage entirely when the hash is unchanged.
- Diff each new snapshot against the previous one as unified text diff. Discard diffs
  under 40 changed characters, and drop lines matching an editable noise.json of regexes
  (dates, cache-busting hashes, view counts, testimonial rotations).
- `watch brief` sends the surviving diffs for the period to Claude or GPT in one call
  and asks for, per competitor: what changed, why it matters, and one suggested response.
  Require a citation back to the exact URL for every claim, and drop any bullet without
  one.
- Render the brief to Markdown in ~/CompetitorBriefs/YYYY-MM-DD.md and send it via SMTP
  from .env. The file is the source of truth, email is just delivery.
- Keep every snapshot and every brief. `watch history <competitor>` prints that rival's
  changes over time, which is the only way a single diff becomes a trend.
- Out of scope: hiring feeds, funding data, traffic estimates, dashboards and any login
  wall. Public pages only, respect robots.txt, one request per URL per run.
- README: setup, a cron line for the weekly run, the per-brief token cost, and a warning
  that month one is mostly tuning noise.json.

## Required capabilities

- an OpenAI or Anthropic API key
- a scheduler and somewhere to keep page snapshots
- a headless browser for pages that render client-side
- SMTP or a Slack webhook for delivery
- patience for the first month of false positives

## 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 Debriefing.

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 =====
# Debriefing product brief

## Problem

Diffing a competitor's pricing page on a cron and asking a model what changed is genuinely an afternoon. changedetection.io will do the watching for you before you write a line. The gap is everything between a diff and a brief. Most page changes are noise: a rotated testimonial, a reordered nav, a CDN hash. Deciding which changes are real, tying them to hiring and funding signals, and turning that into three sentences a founder acts on is judgement encoded over many iterations. Build it and your first month is mostly you deleting alerts about nothing.

## Product outcome

Snapshot each competitor's key pages on a schedule, diff against the last version, and have a model summarise the meaningful changes into a digest.

## Target user

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

## Required capabilities

- an OpenAI or Anthropic API key
- a scheduler and somewhere to keep page snapshots
- a headless browser for pages that render client-side
- SMTP or a Slack webhook for delivery
- patience for the first month of false positives

## Explicit non-goals for v1

- noise filtering, which is the actual product: most diffs are rotated testimonials and changed asset hashes, not competitive moves
- horizon watch, meaning the substitutes and new entrants you did not think to add to the list
- the non-page signals stitched into the same brief: hiring, funding, traffic and LinkedIn movement
- the analytical step from what changed to why it matters to what to do next
- an archive going back far enough that a change reads as a trend rather than an event

## 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 competitor watch that emails me a weekly brief, to replace Debriefing. Requirements:

- Node 22, TypeScript, SQLite via better-sqlite3, Playwright for fetching, node-cron for
  the schedule. CLI only. No accounts, no telemetry, keys in .env.
- competitors.json lists each rival: name, and the URLs that matter (homepage, pricing,
  changelog, careers). Ship it seeded with 3 competitors and 4 URLs each.
- `watch snapshot` fetches every URL with Playwright, strips scripts, styles, nav and
  footer, converts the main content to plain text, and stores it with a SHA-256 hash and
  a timestamp. Skip storage entirely when the hash is unchanged.
- Diff each new snapshot against the previous one as unified text diff. Discard diffs
  under 40 changed characters, and drop lines matching an editable noise.json of regexes
  (dates, cache-busting hashes, view counts, testimonial rotations).
- `watch brief` sends the surviving diffs for the period to Claude or GPT in one call
  and asks for, per competitor: what changed, why it matters, and one suggested response.
  Require a citation back to the exact URL for every claim, and drop any bullet without
  one.
- Render the brief to Markdown in ~/CompetitorBriefs/YYYY-MM-DD.md and send it via SMTP
  from .env. The file is the source of truth, email is just delivery.
- Keep every snapshot and every brief. `watch history <competitor>` prints that rival's
  changes over time, which is the only way a single diff becomes a trend.
- Out of scope: hiring feeds, funding data, traffic estimates, dashboards and any login
  wall. Public pages only, respect robots.txt, one request per URL per run.
- README: setup, a cron line for the weekly run, the per-brief token cost, and a warning
  that month one is mostly tuning noise.json.

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

# Debriefing indie build

## Goal

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

## Scope

Snapshot each competitor's key pages on a schedule, diff against the last version, and have a model summarise the meaningful changes into a digest.

## 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:
- noise filtering, which is the actual product: most diffs are rotated testimonials and changed asset hashes, not competitive moves
- horizon watch, meaning the substitutes and new entrants you did not think to add to the list
- the non-page signals stitched into the same brief: hiring, funding, traffic and LinkedIn movement
- the analytical step from what changed to why it matters to what to do next
- an archive going back far enough that a change reads as a trend rather than an event

If those capabilities are essential, use changedetection.io 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 local competitor watch that emails me a weekly brief, to replace Debriefing. Requirements:

- Node 22, TypeScript, SQLite via better-sqlite3, Playwright for fetching, node-cron for
  the schedule. CLI only. No accounts, no telemetry, keys in .env.
- competitors.json lists each rival: name, and the URLs that matter (homepage, pricing,
  changelog, careers). Ship it seeded with 3 competitors and 4 URLs each.
- `watch snapshot` fetches every URL with Playwright, strips scripts, styles, nav and
  footer, converts the main content to plain text, and stores it with a SHA-256 hash and
  a timestamp. Skip storage entirely when the hash is unchanged.
- Diff each new snapshot against the previous one as unified text diff. Discard diffs
  under 40 changed characters, and drop lines matching an editable noise.json of regexes
  (dates, cache-busting hashes, view counts, testimonial rotations).
- `watch brief` sends the surviving diffs for the period to Claude or GPT in one call
  and asks for, per competitor: what changed, why it matters, and one suggested response.
  Require a citation back to the exact URL for every claim, and drop any bullet without
  one.
- Render the brief to Markdown in ~/CompetitorBriefs/YYYY-MM-DD.md and send it via SMTP
  from .env. The file is the source of truth, email is just delivery.
- Keep every snapshot and every brief. `watch history <competitor>` prints that rival's
  changes over time, which is the only way a single diff becomes a trend.
- Out of scope: hiring feeds, funding data, traffic estimates, dashboards and any login
  wall. Public pages only, respect robots.txt, one request per URL per run.
- README: setup, a cron line for the weekly run, the per-brief token cost, and a warning
  that month one is mostly tuning noise.json.

## Required capabilities

- an OpenAI or Anthropic API key
- a scheduler and somewhere to keep page snapshots
- a headless browser for pages that render client-side
- SMTP or a Slack webhook for delivery
- patience for the first month of false positives

## 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.

# Debriefing product brief

## Problem

Diffing a competitor's pricing page on a cron and asking a model what changed is genuinely an afternoon. changedetection.io will do the watching for you before you write a line. The gap is everything between a diff and a brief. Most page changes are noise: a rotated testimonial, a reordered nav, a CDN hash. Deciding which changes are real, tying them to hiring and funding signals, and turning that into three sentences a founder acts on is judgement encoded over many iterations. Build it and your first month is mostly you deleting alerts about nothing.

## Product outcome

Snapshot each competitor's key pages on a schedule, diff against the last version, and have a model summarise the meaningful changes into a digest.

## Target user

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

## Required capabilities

- an OpenAI or Anthropic API key
- a scheduler and somewhere to keep page snapshots
- a headless browser for pages that render client-side
- SMTP or a Slack webhook for delivery
- patience for the first month of false positives

## Explicit non-goals for v1

- noise filtering, which is the actual product: most diffs are rotated testimonials and changed asset hashes, not competitive moves
- horizon watch, meaning the substitutes and new entrants you did not think to add to the list
- the non-page signals stitched into the same brief: hiring, funding, traffic and LinkedIn movement
- the analytical step from what changed to why it matters to what to do next
- an archive going back far enough that a change reads as a trend rather than an event

## 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 local competitor watch that emails me a weekly brief, to replace Debriefing. Requirements:

- Node 22, TypeScript, SQLite via better-sqlite3, Playwright for fetching, node-cron for
  the schedule. CLI only. No accounts, no telemetry, keys in .env.
- competitors.json lists each rival: name, and the URLs that matter (homepage, pricing,
  changelog, careers). Ship it seeded with 3 competitors and 4 URLs each.
- `watch snapshot` fetches every URL with Playwright, strips scripts, styles, nav and
  footer, converts the main content to plain text, and stores it with a SHA-256 hash and
  a timestamp. Skip storage entirely when the hash is unchanged.
- Diff each new snapshot against the previous one as unified text diff. Discard diffs
  under 40 changed characters, and drop lines matching an editable noise.json of regexes
  (dates, cache-busting hashes, view counts, testimonial rotations).
- `watch brief` sends the surviving diffs for the period to Claude or GPT in one call
  and asks for, per competitor: what changed, why it matters, and one suggested response.
  Require a citation back to the exact URL for every claim, and drop any bullet without
  one.
- Render the brief to Markdown in ~/CompetitorBriefs/YYYY-MM-DD.md and send it via SMTP
  from .env. The file is the source of truth, email is just delivery.
- Keep every snapshot and every brief. `watch history <competitor>` prints that rival's
  changes over time, which is the only way a single diff becomes a trend.
- Out of scope: hiring feeds, funding data, traffic estimates, dashboards and any login
  wall. Public pages only, respect robots.txt, one request per URL per run.
- README: setup, a cron line for the weekly run, the per-brief token cost, and a warning
  that month one is mostly tuning noise.json.

## 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 Debriefing 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