Vibecode Dreams & Stars

You are building a lean indie version of Dreams & Stars.

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 =====
# Dreams & Stars indie build

## Goal

Build the smallest trustworthy replacement for the core Dreams & Stars workflow for one developer or a tiny team.

## Scope

Take a dream description or birth date/time/place, calculate a real natal chart from ephemeris data for astrology, run it through a structured system prompt, and stream back a bilingual interpretation.

## 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:
- the three-layer interpretation methodology (psychological/Jungian, Islamic/Ibn Sirin traditional, actionable) tuned over real usage, not a first draft
- real natal-chart accuracy from ephemeris data instead of an LLM approximating planetary positions
- a spend-reservation system that caps provider cost before generation starts, so one bad request can't blow the budget
- native-quality bilingual Turkish/English copy, not machine-translated
- the credits/paywall, Stripe and RevenueCat payment plumbing

If those capabilities are essential, use swisseph-js/swisseph 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 personal dream-and-astrology reading app to replace Dreams & Stars.

- Next.js 14 App Router + TypeScript + Tailwind, one Postgres database (Supabase or local Postgres). Don't offer alternative stacks.
- Two flows: (1) paste a dream description, (2) enter birth date/time/city for an astrology reading.
- For astrology, install a Swiss Ephemeris TypeScript wrapper (e.g. swisseph-js/swisseph) and actually calculate Sun/Moon/Rising, planetary positions and major aspects from real ephemeris data · never let the model guess planetary positions.
- Write one system prompt per flow. Dream prompt produces three sections: a psychological read (Jungian archetypes, shadow work), a traditional read (folk/Islamic symbolism, framed as interpretation not fortune-telling), and one practical suggestion. Astrology prompt synthesizes the Big Three, then current transits, in that order.
- Call Anthropic or OpenAI with streaming; render the response as it arrives.
- Store every reading (input, output, timestamp) in one `readings` table keyed to a local user id · no auth provider needed for personal use.
- Look up birth-place lat/lon/timezone with a free geocoding API (e.g. Nominatim) · don't hardcode a paid geocoding vendor.
- Support English and Turkish: pass a `language` param into the system prompt and instruct the model to answer entirely in that language, including headings.
- No payments, no credits system, no rate limiting · this is for one person to use for free. Cap output tokens per call so a bug can't run up a large bill.
- Add a simple history page listing past readings.
- .env holds the LLM API key only. No telemetry, no analytics, no third-party scripts.
- Out of scope, on purpose: multi-user accounts, credits/payments, compatibility/synastry readings between two people, a mobile app, and SEO content · those are the parts that turn a personal tool into a product.

## Required capabilities

- Anthropic or OpenAI API key
- an ephemeris library for real planetary positions (Swiss Ephemeris bindings), not LLM-guessed astronomy
- a database for reading history and credit balances
- Stripe or RevenueCat if you want to charge for it

## 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 Dreams & Stars.

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 =====
# Dreams & Stars indie build

## Goal

Build the smallest trustworthy replacement for the core Dreams & Stars workflow for one developer or a tiny team.

## Scope

Take a dream description or birth date/time/place, calculate a real natal chart from ephemeris data for astrology, run it through a structured system prompt, and stream back a bilingual interpretation.

## 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:
- the three-layer interpretation methodology (psychological/Jungian, Islamic/Ibn Sirin traditional, actionable) tuned over real usage, not a first draft
- real natal-chart accuracy from ephemeris data instead of an LLM approximating planetary positions
- a spend-reservation system that caps provider cost before generation starts, so one bad request can't blow the budget
- native-quality bilingual Turkish/English copy, not machine-translated
- the credits/paywall, Stripe and RevenueCat payment plumbing

If those capabilities are essential, use swisseph-js/swisseph 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 personal dream-and-astrology reading app to replace Dreams & Stars.

- Next.js 14 App Router + TypeScript + Tailwind, one Postgres database (Supabase or local Postgres). Don't offer alternative stacks.
- Two flows: (1) paste a dream description, (2) enter birth date/time/city for an astrology reading.
- For astrology, install a Swiss Ephemeris TypeScript wrapper (e.g. swisseph-js/swisseph) and actually calculate Sun/Moon/Rising, planetary positions and major aspects from real ephemeris data · never let the model guess planetary positions.
- Write one system prompt per flow. Dream prompt produces three sections: a psychological read (Jungian archetypes, shadow work), a traditional read (folk/Islamic symbolism, framed as interpretation not fortune-telling), and one practical suggestion. Astrology prompt synthesizes the Big Three, then current transits, in that order.
- Call Anthropic or OpenAI with streaming; render the response as it arrives.
- Store every reading (input, output, timestamp) in one `readings` table keyed to a local user id · no auth provider needed for personal use.
- Look up birth-place lat/lon/timezone with a free geocoding API (e.g. Nominatim) · don't hardcode a paid geocoding vendor.
- Support English and Turkish: pass a `language` param into the system prompt and instruct the model to answer entirely in that language, including headings.
- No payments, no credits system, no rate limiting · this is for one person to use for free. Cap output tokens per call so a bug can't run up a large bill.
- Add a simple history page listing past readings.
- .env holds the LLM API key only. No telemetry, no analytics, no third-party scripts.
- Out of scope, on purpose: multi-user accounts, credits/payments, compatibility/synastry readings between two people, a mobile app, and SEO content · those are the parts that turn a personal tool into a product.

## Required capabilities

- Anthropic or OpenAI API key
- an ephemeris library for real planetary positions (Swiss Ephemeris bindings), not LLM-guessed astronomy
- a database for reading history and credit balances
- Stripe or RevenueCat if you want to charge for it

## 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 Dreams & Stars.

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 =====
# Dreams & Stars product brief

## Problem

The reading loop itself · collect a dream or birth details, prompt an LLM, stream back an interpretation · is a weekend build with any modern coding agent. What resists cloning is the boring half: real natal-chart math from ephemeris data rather than an LLM guessing planetary positions, a prompt methodology (Jungian + Ibn Sirin + actionable layers) tuned over real usage, a budget-reservation system that stops one runaway API call from burning the month's margin, and the credits/payment plumbing. Build the personal version for your own dream journal, but don't expect the DIY build to hold up as a product.

## Product outcome

Take a dream description or birth date/time/place, calculate a real natal chart from ephemeris data for astrology, run it through a structured system prompt, and stream back a bilingual interpretation.

## Target user

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

## Required capabilities

- Anthropic or OpenAI API key
- an ephemeris library for real planetary positions (Swiss Ephemeris bindings), not LLM-guessed astronomy
- a database for reading history and credit balances
- Stripe or RevenueCat if you want to charge for it

## Explicit non-goals for v1

- the three-layer interpretation methodology (psychological/Jungian, Islamic/Ibn Sirin traditional, actionable) tuned over real usage, not a first draft
- real natal-chart accuracy from ephemeris data instead of an LLM approximating planetary positions
- a spend-reservation system that caps provider cost before generation starts, so one bad request can't blow the budget
- native-quality bilingual Turkish/English copy, not machine-translated
- the credits/paywall, Stripe and RevenueCat payment plumbing

## 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 personal dream-and-astrology reading app to replace Dreams & Stars.

- Next.js 14 App Router + TypeScript + Tailwind, one Postgres database (Supabase or local Postgres). Don't offer alternative stacks.
- Two flows: (1) paste a dream description, (2) enter birth date/time/city for an astrology reading.
- For astrology, install a Swiss Ephemeris TypeScript wrapper (e.g. swisseph-js/swisseph) and actually calculate Sun/Moon/Rising, planetary positions and major aspects from real ephemeris data · never let the model guess planetary positions.
- Write one system prompt per flow. Dream prompt produces three sections: a psychological read (Jungian archetypes, shadow work), a traditional read (folk/Islamic symbolism, framed as interpretation not fortune-telling), and one practical suggestion. Astrology prompt synthesizes the Big Three, then current transits, in that order.
- Call Anthropic or OpenAI with streaming; render the response as it arrives.
- Store every reading (input, output, timestamp) in one `readings` table keyed to a local user id · no auth provider needed for personal use.
- Look up birth-place lat/lon/timezone with a free geocoding API (e.g. Nominatim) · don't hardcode a paid geocoding vendor.
- Support English and Turkish: pass a `language` param into the system prompt and instruct the model to answer entirely in that language, including headings.
- No payments, no credits system, no rate limiting · this is for one person to use for free. Cap output tokens per call so a bug can't run up a large bill.
- Add a simple history page listing past readings.
- .env holds the LLM API key only. No telemetry, no analytics, no third-party scripts.
- Out of scope, on purpose: multi-user accounts, credits/payments, compatibility/synastry readings between two people, a mobile app, and SEO content · those are the parts that turn a personal tool into a product.

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

# Dreams & Stars indie build

## Goal

Build the smallest trustworthy replacement for the core Dreams & Stars workflow for one developer or a tiny team.

## Scope

Take a dream description or birth date/time/place, calculate a real natal chart from ephemeris data for astrology, run it through a structured system prompt, and stream back a bilingual interpretation.

## 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:
- the three-layer interpretation methodology (psychological/Jungian, Islamic/Ibn Sirin traditional, actionable) tuned over real usage, not a first draft
- real natal-chart accuracy from ephemeris data instead of an LLM approximating planetary positions
- a spend-reservation system that caps provider cost before generation starts, so one bad request can't blow the budget
- native-quality bilingual Turkish/English copy, not machine-translated
- the credits/paywall, Stripe and RevenueCat payment plumbing

If those capabilities are essential, use swisseph-js/swisseph 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 personal dream-and-astrology reading app to replace Dreams & Stars.

- Next.js 14 App Router + TypeScript + Tailwind, one Postgres database (Supabase or local Postgres). Don't offer alternative stacks.
- Two flows: (1) paste a dream description, (2) enter birth date/time/city for an astrology reading.
- For astrology, install a Swiss Ephemeris TypeScript wrapper (e.g. swisseph-js/swisseph) and actually calculate Sun/Moon/Rising, planetary positions and major aspects from real ephemeris data · never let the model guess planetary positions.
- Write one system prompt per flow. Dream prompt produces three sections: a psychological read (Jungian archetypes, shadow work), a traditional read (folk/Islamic symbolism, framed as interpretation not fortune-telling), and one practical suggestion. Astrology prompt synthesizes the Big Three, then current transits, in that order.
- Call Anthropic or OpenAI with streaming; render the response as it arrives.
- Store every reading (input, output, timestamp) in one `readings` table keyed to a local user id · no auth provider needed for personal use.
- Look up birth-place lat/lon/timezone with a free geocoding API (e.g. Nominatim) · don't hardcode a paid geocoding vendor.
- Support English and Turkish: pass a `language` param into the system prompt and instruct the model to answer entirely in that language, including headings.
- No payments, no credits system, no rate limiting · this is for one person to use for free. Cap output tokens per call so a bug can't run up a large bill.
- Add a simple history page listing past readings.
- .env holds the LLM API key only. No telemetry, no analytics, no third-party scripts.
- Out of scope, on purpose: multi-user accounts, credits/payments, compatibility/synastry readings between two people, a mobile app, and SEO content · those are the parts that turn a personal tool into a product.

## Required capabilities

- Anthropic or OpenAI API key
- an ephemeris library for real planetary positions (Swiss Ephemeris bindings), not LLM-guessed astronomy
- a database for reading history and credit balances
- Stripe or RevenueCat if you want to charge for it

## 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.

# Dreams & Stars product brief

## Problem

The reading loop itself · collect a dream or birth details, prompt an LLM, stream back an interpretation · is a weekend build with any modern coding agent. What resists cloning is the boring half: real natal-chart math from ephemeris data rather than an LLM guessing planetary positions, a prompt methodology (Jungian + Ibn Sirin + actionable layers) tuned over real usage, a budget-reservation system that stops one runaway API call from burning the month's margin, and the credits/payment plumbing. Build the personal version for your own dream journal, but don't expect the DIY build to hold up as a product.

## Product outcome

Take a dream description or birth date/time/place, calculate a real natal chart from ephemeris data for astrology, run it through a structured system prompt, and stream back a bilingual interpretation.

## Target user

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

## Required capabilities

- Anthropic or OpenAI API key
- an ephemeris library for real planetary positions (Swiss Ephemeris bindings), not LLM-guessed astronomy
- a database for reading history and credit balances
- Stripe or RevenueCat if you want to charge for it

## Explicit non-goals for v1

- the three-layer interpretation methodology (psychological/Jungian, Islamic/Ibn Sirin traditional, actionable) tuned over real usage, not a first draft
- real natal-chart accuracy from ephemeris data instead of an LLM approximating planetary positions
- a spend-reservation system that caps provider cost before generation starts, so one bad request can't blow the budget
- native-quality bilingual Turkish/English copy, not machine-translated
- the credits/paywall, Stripe and RevenueCat payment plumbing

## 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 personal dream-and-astrology reading app to replace Dreams & Stars.

- Next.js 14 App Router + TypeScript + Tailwind, one Postgres database (Supabase or local Postgres). Don't offer alternative stacks.
- Two flows: (1) paste a dream description, (2) enter birth date/time/city for an astrology reading.
- For astrology, install a Swiss Ephemeris TypeScript wrapper (e.g. swisseph-js/swisseph) and actually calculate Sun/Moon/Rising, planetary positions and major aspects from real ephemeris data · never let the model guess planetary positions.
- Write one system prompt per flow. Dream prompt produces three sections: a psychological read (Jungian archetypes, shadow work), a traditional read (folk/Islamic symbolism, framed as interpretation not fortune-telling), and one practical suggestion. Astrology prompt synthesizes the Big Three, then current transits, in that order.
- Call Anthropic or OpenAI with streaming; render the response as it arrives.
- Store every reading (input, output, timestamp) in one `readings` table keyed to a local user id · no auth provider needed for personal use.
- Look up birth-place lat/lon/timezone with a free geocoding API (e.g. Nominatim) · don't hardcode a paid geocoding vendor.
- Support English and Turkish: pass a `language` param into the system prompt and instruct the model to answer entirely in that language, including headings.
- No payments, no credits system, no rate limiting · this is for one person to use for free. Cap output tokens per call so a bug can't run up a large bill.
- Add a simple history page listing past readings.
- .env holds the LLM API key only. No telemetry, no analytics, no third-party scripts.
- Out of scope, on purpose: multi-user accounts, credits/payments, compatibility/synastry readings between two people, a mobile app, and SEO content · those are the parts that turn a personal tool into a product.

## 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 Dreams & Stars 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