Vibecode Portfolio Coach

You are building a lean indie version of Portfolio Coach.

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 =====
# Portfolio Coach indie build

## Goal

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

## Scope

Import or enter family holdings, value them, inspect allocation and projections, then ask an AI for a portfolio review grounded in that data.

## 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:
- reliable live pricing and UK fund symbol mapping
- ledger-backed Vanguard history import
- secure cloud accounts, family sharing, and support access
- maintained UK tax and estate-planning assumptions
- hosted AI reviews with current web context

If those capabilities are essential, use Ghostfolio 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-first UK family portfolio tracker like Portfolio Coach. Requirements:

- Next.js 16 App Router + TypeScript, Tailwind, better-sqlite3, and Recharts;
  run locally with `npm run dev` and bind to localhost only.
- Model household members, accounts, and UK wrappers: ISA, SIPP, GIA, pension,
  cash, bonds, and property with mortgages.
- Holdings need ticker, units, cost basis, currency, manual price, and optional
  market price. Always show the quote source and last-updated time.
- Add a CSV importer with saved column mappings and dedupe on a stable row hash.
  Include a mapping for a documented Vanguard transaction CSV example.
- Dashboard: household net worth, value by person, allocation, wrapper split,
  concentration warnings, gain/loss, and stale-price warnings.
- Add editable monthly contributions and a projection chart with retirement age,
  growth, inflation, withdrawals, and planned gifts as explicit assumptions.
- Add a UK planning page for ISA/SIPP/GIA balances and an indicative inheritance-
  tax snapshot. Keep thresholds in one dated config file and label this as
  informational, not financial or tax advice.
- Add an AI review that sends only the calculated portfolio summary to an
  OpenAI-compatible API. Put secrets in `.env.local`; work without AI too.
- Store everything in one local SQLite file and add an encrypted JSON export plus
  a dated backup command. Include a realistic seeded demo household.
- No accounts, telemetry, broker logins, automatic bank sync, or cloud sharing.
  Out of scope: regulated advice and production-grade real-time fund pricing.
- README with setup, CSV format, backup/restore, data limitations, and the exact
  assumptions used by projections and tax estimates.

## Required capabilities

- Node 22
- OpenAI-compatible API key for AI reviews
- optional market-data API key
- local SQLite database

## 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 Portfolio Coach.

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 =====
# Portfolio Coach indie build

## Goal

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

## Scope

Import or enter family holdings, value them, inspect allocation and projections, then ask an AI for a portfolio review grounded in that data.

## 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:
- reliable live pricing and UK fund symbol mapping
- ledger-backed Vanguard history import
- secure cloud accounts, family sharing, and support access
- maintained UK tax and estate-planning assumptions
- hosted AI reviews with current web context

If those capabilities are essential, use Ghostfolio 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-first UK family portfolio tracker like Portfolio Coach. Requirements:

- Next.js 16 App Router + TypeScript, Tailwind, better-sqlite3, and Recharts;
  run locally with `npm run dev` and bind to localhost only.
- Model household members, accounts, and UK wrappers: ISA, SIPP, GIA, pension,
  cash, bonds, and property with mortgages.
- Holdings need ticker, units, cost basis, currency, manual price, and optional
  market price. Always show the quote source and last-updated time.
- Add a CSV importer with saved column mappings and dedupe on a stable row hash.
  Include a mapping for a documented Vanguard transaction CSV example.
- Dashboard: household net worth, value by person, allocation, wrapper split,
  concentration warnings, gain/loss, and stale-price warnings.
- Add editable monthly contributions and a projection chart with retirement age,
  growth, inflation, withdrawals, and planned gifts as explicit assumptions.
- Add a UK planning page for ISA/SIPP/GIA balances and an indicative inheritance-
  tax snapshot. Keep thresholds in one dated config file and label this as
  informational, not financial or tax advice.
- Add an AI review that sends only the calculated portfolio summary to an
  OpenAI-compatible API. Put secrets in `.env.local`; work without AI too.
- Store everything in one local SQLite file and add an encrypted JSON export plus
  a dated backup command. Include a realistic seeded demo household.
- No accounts, telemetry, broker logins, automatic bank sync, or cloud sharing.
  Out of scope: regulated advice and production-grade real-time fund pricing.
- README with setup, CSV format, backup/restore, data limitations, and the exact
  assumptions used by projections and tax estimates.

## Required capabilities

- Node 22
- OpenAI-compatible API key for AI reviews
- optional market-data API key
- local SQLite database

## 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 Portfolio Coach.

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 =====
# Portfolio Coach product brief

## Problem

A private dashboard for holdings, family members, projections, and CSV imports is a credible weekend build. Reliable live pricing for UK funds, a ledger-correct Vanguard importer, household data boundaries, maintained tax rules, and AI advice grounded in every account turn the complete product into a multi-day project.

## Product outcome

Import or enter family holdings, value them, inspect allocation and projections, then ask an AI for a portfolio review grounded in that data.

## Target user

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

## Required capabilities

- Node 22
- OpenAI-compatible API key for AI reviews
- optional market-data API key
- local SQLite database

## Explicit non-goals for v1

- reliable live pricing and UK fund symbol mapping
- ledger-backed Vanguard history import
- secure cloud accounts, family sharing, and support access
- maintained UK tax and estate-planning assumptions
- hosted AI reviews with current web context

## 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-first UK family portfolio tracker like Portfolio Coach. Requirements:

- Next.js 16 App Router + TypeScript, Tailwind, better-sqlite3, and Recharts;
  run locally with `npm run dev` and bind to localhost only.
- Model household members, accounts, and UK wrappers: ISA, SIPP, GIA, pension,
  cash, bonds, and property with mortgages.
- Holdings need ticker, units, cost basis, currency, manual price, and optional
  market price. Always show the quote source and last-updated time.
- Add a CSV importer with saved column mappings and dedupe on a stable row hash.
  Include a mapping for a documented Vanguard transaction CSV example.
- Dashboard: household net worth, value by person, allocation, wrapper split,
  concentration warnings, gain/loss, and stale-price warnings.
- Add editable monthly contributions and a projection chart with retirement age,
  growth, inflation, withdrawals, and planned gifts as explicit assumptions.
- Add a UK planning page for ISA/SIPP/GIA balances and an indicative inheritance-
  tax snapshot. Keep thresholds in one dated config file and label this as
  informational, not financial or tax advice.
- Add an AI review that sends only the calculated portfolio summary to an
  OpenAI-compatible API. Put secrets in `.env.local`; work without AI too.
- Store everything in one local SQLite file and add an encrypted JSON export plus
  a dated backup command. Include a realistic seeded demo household.
- No accounts, telemetry, broker logins, automatic bank sync, or cloud sharing.
  Out of scope: regulated advice and production-grade real-time fund pricing.
- README with setup, CSV format, backup/restore, data limitations, and the exact
  assumptions used by projections and tax estimates.

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

# Portfolio Coach indie build

## Goal

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

## Scope

Import or enter family holdings, value them, inspect allocation and projections, then ask an AI for a portfolio review grounded in that data.

## 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:
- reliable live pricing and UK fund symbol mapping
- ledger-backed Vanguard history import
- secure cloud accounts, family sharing, and support access
- maintained UK tax and estate-planning assumptions
- hosted AI reviews with current web context

If those capabilities are essential, use Ghostfolio 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-first UK family portfolio tracker like Portfolio Coach. Requirements:

- Next.js 16 App Router + TypeScript, Tailwind, better-sqlite3, and Recharts;
  run locally with `npm run dev` and bind to localhost only.
- Model household members, accounts, and UK wrappers: ISA, SIPP, GIA, pension,
  cash, bonds, and property with mortgages.
- Holdings need ticker, units, cost basis, currency, manual price, and optional
  market price. Always show the quote source and last-updated time.
- Add a CSV importer with saved column mappings and dedupe on a stable row hash.
  Include a mapping for a documented Vanguard transaction CSV example.
- Dashboard: household net worth, value by person, allocation, wrapper split,
  concentration warnings, gain/loss, and stale-price warnings.
- Add editable monthly contributions and a projection chart with retirement age,
  growth, inflation, withdrawals, and planned gifts as explicit assumptions.
- Add a UK planning page for ISA/SIPP/GIA balances and an indicative inheritance-
  tax snapshot. Keep thresholds in one dated config file and label this as
  informational, not financial or tax advice.
- Add an AI review that sends only the calculated portfolio summary to an
  OpenAI-compatible API. Put secrets in `.env.local`; work without AI too.
- Store everything in one local SQLite file and add an encrypted JSON export plus
  a dated backup command. Include a realistic seeded demo household.
- No accounts, telemetry, broker logins, automatic bank sync, or cloud sharing.
  Out of scope: regulated advice and production-grade real-time fund pricing.
- README with setup, CSV format, backup/restore, data limitations, and the exact
  assumptions used by projections and tax estimates.

## Required capabilities

- Node 22
- OpenAI-compatible API key for AI reviews
- optional market-data API key
- local SQLite database

## 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.

# Portfolio Coach product brief

## Problem

A private dashboard for holdings, family members, projections, and CSV imports is a credible weekend build. Reliable live pricing for UK funds, a ledger-correct Vanguard importer, household data boundaries, maintained tax rules, and AI advice grounded in every account turn the complete product into a multi-day project.

## Product outcome

Import or enter family holdings, value them, inspect allocation and projections, then ask an AI for a portfolio review grounded in that data.

## Target user

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

## Required capabilities

- Node 22
- OpenAI-compatible API key for AI reviews
- optional market-data API key
- local SQLite database

## Explicit non-goals for v1

- reliable live pricing and UK fund symbol mapping
- ledger-backed Vanguard history import
- secure cloud accounts, family sharing, and support access
- maintained UK tax and estate-planning assumptions
- hosted AI reviews with current web context

## 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-first UK family portfolio tracker like Portfolio Coach. Requirements:

- Next.js 16 App Router + TypeScript, Tailwind, better-sqlite3, and Recharts;
  run locally with `npm run dev` and bind to localhost only.
- Model household members, accounts, and UK wrappers: ISA, SIPP, GIA, pension,
  cash, bonds, and property with mortgages.
- Holdings need ticker, units, cost basis, currency, manual price, and optional
  market price. Always show the quote source and last-updated time.
- Add a CSV importer with saved column mappings and dedupe on a stable row hash.
  Include a mapping for a documented Vanguard transaction CSV example.
- Dashboard: household net worth, value by person, allocation, wrapper split,
  concentration warnings, gain/loss, and stale-price warnings.
- Add editable monthly contributions and a projection chart with retirement age,
  growth, inflation, withdrawals, and planned gifts as explicit assumptions.
- Add a UK planning page for ISA/SIPP/GIA balances and an indicative inheritance-
  tax snapshot. Keep thresholds in one dated config file and label this as
  informational, not financial or tax advice.
- Add an AI review that sends only the calculated portfolio summary to an
  OpenAI-compatible API. Put secrets in `.env.local`; work without AI too.
- Store everything in one local SQLite file and add an encrypted JSON export plus
  a dated backup command. Include a realistic seeded demo household.
- No accounts, telemetry, broker logins, automatic bank sync, or cloud sharing.
  Out of scope: regulated advice and production-grade real-time fund pricing.
- README with setup, CSV format, backup/restore, data limitations, and the exact
  assumptions used by projections and tax estimates.

## 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 Portfolio Coach 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