.cursorrules

# .cursorrules

Behavioral guidelines for Windsurf / Cursor legacy fallback in this project. These reduce common LLM coding mistakes and enforce controlled AI-assisted development.

<!-- Generated by scripts/generate-rules.py; edit source files instead. -->

**Framework:** AI-Coding-Standards v2.6.1 with 6 Core Principles
**Governance:** Controlled AI-Assisted Development (vibe-proof approach)

---

## Core Principles (Non-Negotiable)

## 1. Think Before Coding

**Don't assume. Don't hide confusion. Surface tradeoffs.**

Before implementing:
- State your assumptions explicitly. If uncertain, ask.
- If multiple interpretations exist, present them - don't pick silently.
- If a simpler approach exists, say so. Push back when warranted.
- If something is unclear, stop. Name what's confusing. Ask.

## 2. Simplicity First

**Minimum code that solves the problem. Nothing speculative.**

- No features beyond what was asked.
- No abstractions for single-use code.
- No "flexibility" or "configurability" that wasn't requested.
- No error handling for impossible scenarios.
- If you write 200 lines and it could be 50, rewrite it.

Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.

## 3. Surgical Changes

**Touch only what you must. Clean up only your own mess.**

When editing existing code:
- Don't "improve" adjacent code, comments, or formatting.
- Don't refactor things that aren't broken.
- Match existing style, even if you'd do it differently.
- If you notice unrelated dead code, mention it - don't delete it.

When your changes create orphans:
- Remove imports/variables/functions that YOUR changes made unused.
- Don't remove pre-existing dead code unless asked.

The test: Every changed line should trace directly to the user's request.

## 4. Goal-Driven Execution

**Define success criteria. Loop until verified.**

Transform tasks into verifiable goals:
- "Add validation" -> "Write tests for invalid inputs, then make them pass"
- "Fix the bug" -> "Write a test that reproduces it, then make it pass"
- "Refactor X" -> "Ensure tests pass before and after"

For multi-step tasks, state a brief plan:
```
1. [Step] -> verify: [check]
2. [Step] -> verify: [check]
3. [Step] -> verify: [check]
```

Strong success criteria let you loop independently. Weak criteria ("make it work") require constant clarification.

## 5. DRY & Reusability

**Never duplicate UI, logic, configurations, types, or any code. Always use shared systems.**

- **UI/Styling & Assets:** Always utilize the project's existing design system, shared assets, or global CSS variables. Do not hardcode disjointed styles or create duplicate UI components.
- **Logic & Functions:** Extract any logic or calculations used 2+ times into pure, reusable functions within the project's established shared directories. Do not repeat the same logic blocks.
- **Configurations & Metadata:** Centralize environment variables, configuration schemas, build scripts, and metadata. Avoid duplicating configurations across environments or services.
- **Types & Schemas:** Define models, interfaces, and schemas in shared folders. Reuse and extend existing types instead of recreating them.
- **Tests & Mock Data:** Share test utilities, mock data factories, and assertion helpers. Do not duplicate test setups or mock data structures.

## 6. Code Organization

**Don't put all code in one file. Separate into multiple files with general names.**

- **File Size Limit:** Keep files focused and readable. As a guideline, split files when they exceed **300 lines of code (LOC)**.
- **Concern Separation:** Separate distinct concerns (e.g. data schema, request handling, business logic, UI, utilities) into separate directories or files.
- **General & Suffix Naming:** Group similar functions in files with general, purpose-driven names and consistent suffixes (e.g. `auth.service.ts`, `math.helper.ts`, `user.model.ts`).
- **Co-locate Related Files:** Keep tests, styles, and local helpers close to their main component or module rather than in distant folders.

## Self-Check Report

After completing code, include:
- Requirements met? [list]
- Could this be simpler? [yes/no]
- All changes trace to request? [yes/no]
- Success criteria verified? [how]

## Dynamic Skill Auto-Discovery

For task-specific workflow capsules, check [SKILL-REFERENCE.md](SKILL-REFERENCE.md) and load the matching [skills/](skills/) `SKILL.md` only when the task matches its trigger.

Read the relevant standard before executing when the user's request involves:

- **Tests/TDD:** [ai-agent-standards/engineering-practices/TESTING_STANDARDS.md](ai-agent-standards/engineering-practices/TESTING_STANDARDS.md)
- **Security/Auth/Secrets:** [ai-agent-standards/risk-management/security-constraints.md](ai-agent-standards/risk-management/security-constraints.md)
- **Performance/Database/Caching:** [ai-agent-standards/engineering-practices/NON_FUNCTIONAL_REQUIREMENTS.md](ai-agent-standards/engineering-practices/NON_FUNCTIONAL_REQUIREMENTS.md)
- **UI/Accessibility:** [ai-agent-standards/compliance/A11Y_CHECKLIST.md](ai-agent-standards/compliance/A11Y_CHECKLIST.md)
- **Release/Git/CI:** [ai-agent-standards/engineering-practices/RELEASE_PROCESS.md](ai-agent-standards/engineering-practices/RELEASE_PROCESS.md)
- **Docs/README/Changelog:** [ai-agent-standards/engineering-practices/DOCUMENTATION_STANDARDS.md](ai-agent-standards/engineering-practices/DOCUMENTATION_STANDARDS.md)
- **Compliance/Audit:** [ai-agent-standards/compliance/COMPLIANCE.md](ai-agent-standards/compliance/COMPLIANCE.md)

## Verification

When asked "What coding standards are you following?" or "/standards", respond:

> AI-Coding-Standards v2.6.1 with 6 Core Principles active.
> Framework: Controlled AI-Assisted Development
> Principles: (1) Think Before Coding, (2) Simplicity First, (3) Surgical Changes, (4) Goal-Driven Execution, (5) DRY & Reusability, (6) Code Organization