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codeflash-internal/CLAUDE.md
Kevin Turcios 4c3deeb7b8
Restructure CLAUDE.md files and add path-scoped rules for monorepo (#2417) 
## Summary

- Restructure CLAUDE.md hierarchy so Claude Code auto-discovers
project-specific instructions
- Delete dead `AGENTS.md` files (referenced non-existent
`.tessl/RULES.md`)
- Rename `django/aiservice/AGENTS.md` → `CLAUDE.md` for auto-discovery
- Create `js/CLAUDE.md` with package commands and gotchas
- Move PR review guidelines to `.claude/rules/pr-review.md` (auto-loaded
rule)
- Move prek workflow to `.claude/skills/fix-prek.md` (on-demand skill)
- Add path-scoped rules for Python and Next.js patterns
- Add domain glossary, service architecture diagram, and per-package
gotchas

## Test plan

- Verify `CLAUDE.md` files exist at root, `django/aiservice/`, and `js/`
- Verify no remaining references to `AGENTS.md` or `.tessl/`
- Verify `.claude/rules/` and `.claude/skills/` files are committed
2026-02-14 17:13:09 -05:00

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Claude Code Instructions

Monorepo Structure

codeflash-internal/
├── django/aiservice/   # Python backend — Django-Ninja API for LLM optimization
├── js/
│   ├── cf-api/         # Express API — GitHub webhooks, PR analysis, DB ops
│   ├── cf-webapp/      # Next.js 14 — Dashboard UI
│   ├── common/         # Shared library — Prisma schema, types, integrations
│   └── VSC-Extension/  # VS Code extension — in-editor optimization
├── cli/                # Java/Gradle — sample code-to-optimize for testing
├── deployment/         # Unified Docker container (on-prem) + Azure configs
└── experiments/        # R&D — Jupyter notebooks, analysis scripts

Service Architecture

VSC-Extension / CLI → cf-api (Express, :3001) → aiservice (Django-Ninja, :8000)
                      cf-webapp (:3000) reads from the same PostgreSQL DB via Prisma

Shared Tooling

  • Python: Use uv for dependency management and script execution. Never use pip.
  • JavaScript: Use npm for all JS packages.
  • Pre-commit: uv run prek run --all-files from repo root.

Git Commits

Use conventional commit format: fix:, feat:, refactor:, docs:, test:, chore:

Glossary

  • Function to Optimize — target function for optimization
  • Optimization Candidate — LLM-generated code that may be faster
  • Read-Write Context — code the LLM can modify
  • Read-Only Context — code provided as info only (not modified)
  • Tracer — collects input args for a Python function at runtime
  • Replay Test — reruns traced inputs to verify behavior
  • Inspired Regression Test — new tests generated by the LLM from existing tests + function code
  • Comparator — compares two Python objects for equality