Define OpenSpec change for monthly expense tracker v1

.gitignore

@@ -0,0 +1,9 @@
+.next/
+node_modules/
+.env
+.env.local
+prisma/dev.db
+prisma/dev.db-journal
+.opencode/
+.claude/
+.codex/

openspec/changes/monthly-expense-tracker-v1/.openspec.yaml

@@ -0,0 +1,2 @@
+schema: spec-driven
+created: 2026-03-23

openspec/changes/monthly-expense-tracker-v1/design.md

@@ -0,0 +1,63 @@
+## Context
+
+The repository starts with a product plan and OpenSpec configuration but no application code. The first version needs a complete local-first implementation using `Next.js`, `Prisma`, `SQLite`, and `OpenAI`, while keeping scope intentionally narrow: one user, manual data entry, fixed categories, and dashboard-only insights. Month boundaries are based on the local machine timezone, which affects date parsing, monthly aggregation, and paycheck coverage calculations.
+
+## Goals / Non-Goals
+
+**Goals:**
+- Build a single deployable `Next.js` app with UI views and server routes in one codebase.
+- Persist expenses, paychecks, and generated monthly insights in a local SQLite database managed by Prisma.
+- Centralize monthly aggregation logic so dashboard reads and AI generation use the same numbers.
+- Keep AI integration isolated behind a small service layer that prepares structured monthly context and calls `OpenAI`.
+- Make v1 testable with deterministic validation, aggregation, and safe fallback behavior for sparse data.
+
+**Non-Goals:**
+- Authentication, multi-user support, bank sync, receipt scanning, background jobs, or email delivery.
+- Automatic categorization, editing data through AI, or free-form custom categories in v1.
+- Complex financial forecasting beyond simple next-month guidance derived from recent activity.
+
+## Decisions
+
+### Use a single `Next.js` app for UI and APIs
+- Rationale: the project is small, local-first, and benefits from one codebase for pages, route handlers, and shared utilities.
+- Alternative considered: separate frontend and API service. Rejected because it adds deployment and data-sharing complexity without helping the v1 scope.
+
+### Use Prisma with SQLite for persistence
+- Rationale: Prisma provides schema management, typed queries, and straightforward migrations while keeping SQLite as a simple embedded database.
+- Alternative considered: raw SQLite queries. Rejected because it slows down schema evolution and validation during initial development.
+
+### Store money as integer cents and dates as local calendar strings
+- Rationale: integer cents avoid floating-point issues, and local-date strings such as `YYYY-MM-DD` align with the local machine timezone requirement for monthly boundaries.
+- Alternative considered: floating-point amounts or UTC timestamps only. Rejected because both introduce avoidable ambiguity for monthly reporting.
+
+### Put aggregation logic in shared server-side services
+- Rationale: dashboard totals, paycheck coverage, category breakdowns, and AI snapshots must stay consistent across endpoints.
+- Alternative considered: separate logic per route. Rejected because it risks drift between dashboard and insight generation.
+
+### Add an AI service boundary with structured prompt input and fallback responses
+- Rationale: the app needs provider isolation, predictable prompt shape, and safe messaging when data is too sparse for useful advice.
+- Alternative considered: calling `OpenAI` directly from a route handler with raw records. Rejected because it couples prompting, aggregation, and transport too tightly.
+
+## Risks / Trade-offs
+
+- [Local timezone handling differs by machine] -> Normalize month calculations around stored local-date strings and test month edges explicitly.
+- [SQLite limits concurrency] -> Acceptable for single-user local-first v1; no mitigation beyond keeping writes simple.
+- [AI output quality varies with sparse or noisy data] -> Add minimum-data fallback logic and keep prompts grounded in structured aggregates.
+- [OpenAI dependency requires API key management] -> Read configuration from environment variables and keep failure messages explicit in the UI/API.
+
+## Migration Plan
+
+1. Scaffold the `Next.js` app and install core dependencies.
+2. Add the Prisma schema, create the initial SQLite migration, and generate the client.
+3. Implement CRUD routes and UI forms for expenses and paychecks.
+4. Implement dashboard aggregation and month filtering.
+5. Add the AI insight service and persistence for generated monthly insights.
+6. Run automated tests, then exercise the main flows in the browser.
+
+Rollback is straightforward in early development: revert the code change and reset the local SQLite database if schema changes become invalid.
+
+## Open Questions
+
+- Which `OpenAI` model should be the initial default for monthly insight generation?
+- Should generated monthly insights overwrite prior insights for the same month or create a historical trail of regenerated summaries?
+- Do we want soft confirmation in the UI before deleting expenses or paychecks, or is immediate deletion acceptable for v1?

openspec/changes/monthly-expense-tracker-v1/proposal.md

@@ -0,0 +1,28 @@
+## Why
+
+The project currently has a product plan but no runnable application, spec artifacts, or implementation scaffold. Formalizing the first version now creates a clear contract for building a local-first expense tracker with reliable monthly summaries and AI-generated guidance.
+
+## What Changes
+
+- Add a local-first web app for tracking expenses and biweekly paychecks without authentication.
+- Add dashboard capabilities for month-to-date totals, category breakdowns, cash flow, and spending comparisons.
+- Add manual AI insight generation for a selected month using structured aggregates and transaction samples.
+- Add local persistence, validation, and API routes for expenses, paychecks, dashboard data, and insight generation.
+
+## Capabilities
+
+### New Capabilities
+- `expense-tracking`: Record, list, and delete categorized expenses for a given date.
+- `paycheck-tracking`: Record, list, and delete paycheck entries based on actual pay dates.
+- `monthly-dashboard`: View month-specific spending, income, and derived financial summaries.
+- `monthly-insights`: Generate read-only AI insights from monthly financial activity.
+
+### Modified Capabilities
+- None.
+
+## Impact
+
+- Affected code: new `Next.js` application, server routes, UI views, Prisma schema, and AI integration service.
+- APIs: `POST/GET/DELETE` routes for expenses and paychecks, `GET /dashboard`, and `POST /insights/generate`.
+- Dependencies: `Next.js`, `Prisma`, `SQLite`, and `OpenAI` SDK.
+- Systems: local machine timezone handling for month boundaries and persisted local database storage.

openspec/changes/monthly-expense-tracker-v1/specs/expense-tracking/spec.md

@@ -0,0 +1,23 @@
+## ADDED Requirements
+
+### Requirement: User can record categorized expenses
+The system SHALL allow the user to create an expense with a title, amount, category, and local calendar date using fixed starter categories.
+
+#### Scenario: Valid expense is created
+- **WHEN** the user submits a title, positive amount, valid category, and valid local date
+- **THEN** the system stores the expense and returns the created record
+
+#### Scenario: Invalid expense is rejected
+- **WHEN** the user submits a missing title, invalid amount, invalid category, or invalid date
+- **THEN** the system rejects the request with a validation error and does not store the expense
+
+### Requirement: User can review and delete expenses
+The system SHALL allow the user to list recorded expenses and delete a specific expense by identifier.
+
+#### Scenario: Expenses are listed
+- **WHEN** the user requests expenses for the app
+- **THEN** the system returns stored expenses in a stable order with their recorded fields
+
+#### Scenario: Expense is deleted
+- **WHEN** the user deletes an existing expense
+- **THEN** the system removes that expense and it no longer appears in future listings or aggregates

openspec/changes/monthly-expense-tracker-v1/specs/monthly-dashboard/spec.md

@@ -0,0 +1,23 @@
+## ADDED Requirements
+
+### Requirement: Dashboard shows month-specific financial totals
+The system SHALL return month-specific dashboard data for a requested `YYYY-MM` month using the local machine timezone for month boundaries.
+
+#### Scenario: Dashboard totals are calculated for a populated month
+- **WHEN** the user requests the dashboard for a month with expenses and paychecks
+- **THEN** the system returns total expenses, total paychecks, net cash flow, and a category breakdown for that month
+
+#### Scenario: Dashboard supports partial current-month data
+- **WHEN** the user requests the dashboard for the current month before the month is complete
+- **THEN** the system returns meaningful month-to-date totals and comparisons using the transactions recorded so far
+
+### Requirement: Dashboard includes derived spending comparisons
+The system SHALL provide derived comparisons for the selected month, including highest category, largest expense, average daily spend, and paycheck coverage information.
+
+#### Scenario: Derived comparisons are available
+- **WHEN** the selected month contains enough data for comparisons
+- **THEN** the system returns the highest category, largest single expense, average daily spend, and spend-versus-paycheck coverage values
+
+#### Scenario: Derived comparisons degrade safely for sparse data
+- **WHEN** the selected month has no expenses or otherwise insufficient data for a comparison
+- **THEN** the system returns null or empty-safe comparison fields instead of failing

openspec/changes/monthly-expense-tracker-v1/specs/monthly-insights/spec.md

@@ -0,0 +1,23 @@
+## ADDED Requirements
+
+### Requirement: User can generate monthly AI insights on demand
+The system SHALL allow the user to manually generate AI insights for any month with existing or sparse data by sending structured monthly context to the configured `OpenAI` provider.
+
+#### Scenario: Insights are generated for a month with data
+- **WHEN** the user requests insight generation for a month with recorded activity
+- **THEN** the system sends monthly aggregates plus transaction samples to the AI service and returns a rendered narrative summary with structured supporting totals
+
+#### Scenario: Prior month insights can be generated
+- **WHEN** the user requests insight generation for a previous month that has recorded data
+- **THEN** the system generates and stores insight output for that requested month
+
+### Requirement: Insight generation is read-only and safe for sparse months
+The system SHALL keep AI insight generation read-only and return a safe fallback summary when a month does not have enough data for meaningful guidance.
+
+#### Scenario: Sparse month returns fallback insight
+- **WHEN** the user requests insight generation for a month with empty or near-empty data
+- **THEN** the system returns a fallback message instead of low-confidence advice
+
+#### Scenario: AI does not mutate financial records
+- **WHEN** the system generates or stores monthly insights
+- **THEN** no expense or paycheck records are created, updated, or deleted as part of that request

openspec/changes/monthly-expense-tracker-v1/specs/paycheck-tracking/spec.md

@@ -0,0 +1,23 @@
+## ADDED Requirements
+
+### Requirement: User can record paychecks by pay date
+The system SHALL allow the user to create a paycheck with a positive amount and a local pay date.
+
+#### Scenario: Valid paycheck is created
+- **WHEN** the user submits a positive amount and valid local pay date
+- **THEN** the system stores the paycheck and returns the created record
+
+#### Scenario: Invalid paycheck is rejected
+- **WHEN** the user submits a missing or invalid amount or date
+- **THEN** the system rejects the request with a validation error and does not store the paycheck
+
+### Requirement: User can review and delete paychecks
+The system SHALL allow the user to list recorded paychecks and delete a specific paycheck by identifier.
+
+#### Scenario: Paychecks are listed
+- **WHEN** the user requests paychecks for the app
+- **THEN** the system returns stored paychecks in a stable order with their recorded fields
+
+#### Scenario: Paycheck is deleted
+- **WHEN** the user deletes an existing paycheck
+- **THEN** the system removes that paycheck and it no longer appears in future dashboard totals or insight inputs

openspec/changes/monthly-expense-tracker-v1/tasks.md

@@ -0,0 +1,31 @@
+## 1. Project setup
+
+- [ ] 1.1 Scaffold the `Next.js` app with TypeScript, linting, and baseline project configuration.
+- [ ] 1.2 Add runtime dependencies for Prisma, SQLite, validation, charts, and `OpenAI` integration.
+- [ ] 1.3 Add development dependencies and scripts for testing, Prisma generation, and local development.
+- [ ] 1.4 Add base environment and ignore-file setup for local database and API key configuration.
+
+## 2. Persistence and shared services
+
+- [ ] 2.1 Define Prisma models for `Expense`, `Paycheck`, and `MonthlyInsight` and create the initial SQLite migration.
+- [ ] 2.2 Implement shared validation schemas for expenses, paychecks, and month query parameters.
+- [ ] 2.3 Implement shared money and local-date utilities for month boundary calculations.
+
+## 3. Expense and paycheck workflows
+
+- [ ] 3.1 Implement expense API routes for create, list, and delete operations.
+- [ ] 3.2 Implement paycheck API routes for create, list, and delete operations.
+- [ ] 3.3 Build the `Add Expense` view with form submission, validation feedback, and expense listing.
+- [ ] 3.4 Build the `Income/Paychecks` view with form submission, validation feedback, and paycheck listing.
+
+## 4. Dashboard and insights
+
+- [ ] 4.1 Implement monthly dashboard aggregation services for totals, category breakdowns, and derived comparisons.
+- [ ] 4.2 Implement the dashboard API route and render dashboard sections for month-to-date metrics and comparisons.
+- [ ] 4.3 Implement the `OpenAI` insight service with structured monthly snapshot input and sparse-month fallback logic.
+- [ ] 4.4 Implement insight generation and display in the dashboard, including persisted monthly insight records.
+
+## 5. Verification
+
+- [ ] 5.1 Add automated tests for validation, persistence, dashboard aggregates, and insight fallback behavior.
+- [ ] 5.2 Verify the primary user flows in the browser, including expense entry, paycheck entry, dashboard updates, and insight generation.

openspec/config.yaml

@@ -0,0 +1,20 @@
+schema: spec-driven
+
+# Project context (optional)
+# This is shown to AI when creating artifacts.
+# Add your tech stack, conventions, style guides, domain knowledge, etc.
+# Example:
+#   context: |
+#     Tech stack: TypeScript, React, Node.js
+#     We use conventional commits
+#     Domain: e-commerce platform
+
+# Per-artifact rules (optional)
+# Add custom rules for specific artifacts.
+# Example:
+#   rules:
+#     proposal:
+#       - Keep proposals under 500 words
+#       - Always include a "Non-goals" section
+#     tasks:
+#       - Break tasks into chunks of max 2 hours

plan.md

@@ -0,0 +1,81 @@
+# Monthly Expense Tracker With AI Insights
+
+## Summary
+Build a single-user, local-first web app for manually recording daily expenses and biweekly paychecks, then generating month-to-date and end-of-month spending insights with next-month guidance.
+
+The first version is optimized for fast daily entry and a dashboard-first review flow. It uses fixed starter categories, a simple local database, and an in-app AI summary rather than email or exports.
+
+## Implementation Changes
+- App shape:
+  - Build a web app with 3 primary views: `Dashboard`, `Add Expense`, and `Income/Paychecks`.
+  - Keep it single-user and local-first with no authentication in v1.
+- Core data model:
+  - `Expense`: `id`, `date`, `title`, `amount`, `category`, `createdAt`.
+  - `Paycheck`: `id`, `payDate`, `amount`, `createdAt`.
+  - `MonthlyInsight`: `id`, `month`, `year`, `generatedAt`, `summary`, `recommendations`, `inputSnapshot`.
+- Categories:
+  - Ship with fixed starter categories such as `Rent`, `Food`, `Transport`, `Bills`, `Shopping`, `Health`, `Entertainment`, `Misc`.
+  - Store category as a controlled value so monthly summaries can group reliably.
+- Dashboard behavior:
+  - Show current month totals for expenses, category breakdown, paycheck total, and net cash flow.
+  - Include month-to-date charts and simple comparisons like highest category, largest single expense, average daily spend, and spend vs paycheck coverage.
+  - Provide a `Generate Insights` action that works any time during the month, not only at month-end.
+- AI insight generation:
+  - Build a summarization pipeline that prepares structured monthly aggregates plus recent transaction samples, then sends that context to the AI model.
+  - Ask the model to return:
+    - spending pattern summary
+    - unusual categories or spikes
+    - paycheck-to-spend timing observations
+    - practical next-month suggestions
+  - Keep AI read-only in v1: it does not edit data or auto-categorize entries.
+- Storage and architecture:
+  - Use a simple embedded database for local-first persistence, preferably SQLite.
+  - Implement the app with `Next.js` for the web UI and server routes.
+  - Use `Prisma` for the data layer and migrations.
+  - Keep the AI integration behind a small service boundary so the model/provider can be swapped later without changing UI code.
+  - Use `OpenAI` for insight generation in v1.
+- Public interfaces / APIs:
+  - `POST /expenses`, `GET /expenses`, `DELETE /expenses/:id`
+  - `POST /paychecks`, `GET /paychecks`, `DELETE /paychecks/:id`
+  - `GET /dashboard?month=YYYY-MM`
+  - `POST /insights/generate?month=YYYY-MM`
+  - Insight response should include structured fields for totals and a rendered narrative summary for the dashboard.
+
+## Implementation Checklist
+- [ ] Scaffold the `Next.js` app and set up base project config.
+- [ ] Add `Prisma` with a SQLite database and define `Expense`, `Paycheck`, and `MonthlyInsight` models.
+- [ ] Build shared validation and month/date helpers using local machine time.
+- [ ] Implement expense CRUD routes and forms.
+- [ ] Implement paycheck CRUD routes and forms.
+- [ ] Build dashboard aggregation logic for totals, categories, cash flow, and comparisons.
+- [ ] Add the insight generation service boundary and `OpenAI` integration.
+- [ ] Render AI insight output in the dashboard with fallback behavior for sparse months.
+- [ ] Add tests for validation, aggregates, persistence, and insight generation.
+- [ ] Verify all month-boundary behavior using local timezone dates.
+
+## Test Plan
+- Expense entry:
+  - Create valid expense with title, amount, date, and category.
+  - Reject missing or invalid amount/date/category.
+- Paycheck tracking:
+  - Record multiple biweekly paychecks in one month and across month boundaries.
+  - Verify dashboard cash-flow totals use actual paycheck dates, not monthly averaging.
+- Dashboard calculations:
+  - Category totals, monthly totals, average daily spend, and net cash flow are correct.
+  - Current-month partial data still renders meaningful month-to-date views.
+- Insight generation:
+  - AI request uses aggregated monthly inputs plus transaction samples.
+  - Manual generation works for current month and prior months with existing data.
+  - Empty or near-empty months return a safe fallback message instead of low-quality advice.
+- Persistence:
+  - Data remains available after app restart.
+  - Deleting an expense or paycheck updates dashboard and future insight results correctly.
+
+## Assumptions And Defaults
+- First version is for your own use only, with no login or multi-user support.
+- Expense entry is fully manual; receipt scanning and bank sync are out of scope.
+- AI insights appear only inside the dashboard.
+- The app supports month-to-date previews as well as end-of-month review.
+- Fixed starter categories are sufficient for v1; custom categories can be added later.
+- Income is modeled as discrete biweekly paychecks because that materially affects next-month guidance and intra-month cash-flow interpretation.
+- Month and paycheck boundaries use the local machine timezone.