A Claude Code skill that writes your CLAUDE.md, .claude/rules/, and .claude/agents/ files for you — grounded in Anthropic's official best practices.
You describe your project. Prompting Buddy scans your repo, asks a few sharp questions, and writes prompt files directly into your project. No copy-paste, no guesswork about what belongs in CLAUDE.md vs rules vs agents.
- Fetches the latest official docs from Anthropic before writing anything — so the advice never goes stale
- Scans your repo to detect tech stack, build tools, linting config, CI setup, and existing prompt files
- Asks targeted questions to fill gaps the code doesn't reveal (workflow, conventions, team quirks)
- Generates prompt files — CLAUDE.md under 200 lines, path-scoped rules, properly formatted agent definitions
- Self-reviews against a checklist before writing: no codebase tours, no teaching basics, no bloat
- Writes files directly into your project — or falls back to markdown blocks if you prefer
It also reviews and optimizes existing CLAUDE.md files — trimming redundant emphasis, removing self-evident rules, and restructuring for better adherence.
Download the latest prompting-buddy.skill from Releases, then in Claude Code:
/skill install path/to/prompting-buddy.skill
Or clone this repo into your skills directory:
git clone https://github.com/YOUR_USERNAME/prompting-buddy.git ~/.claude/skills/prompting-buddyOnce installed, the skill triggers automatically when you ask Claude Code things like:
- "Set up CLAUDE.md for this project"
- "I need rules files scoped to each service in my monorepo"
- "Create a code-review agent"
- "My CLAUDE.md is too long and Claude keeps ignoring half of it — fix it"
- "Migrate my .cursorrules to Claude Code"
Or invoke it directly:
/prompting-buddy set up Claude Code for this project
> I have a Python monorepo with api-gateway (FastAPI), ml-pipeline (PyTorch),
> and data-ingestion (Airflow). Each has different conventions. Set me up.
Prompting Buddy generates:
Created:
./CLAUDE.md (78 lines)
./.claude/rules/api-gateway.md (24 lines, paths: services/api-gateway/**)
./.claude/rules/ml-pipeline.md (18 lines, paths: services/ml-pipeline/**)
./.claude/rules/data-ingestion.md (20 lines, paths: services/data-ingestion/**)
./.claude/agents/code-reviewer.md (32 lines, model: sonnet, read-only)
The best way to improve this skill is to run evals, review the outputs, and iterate on SKILL.md. If Claude generates bad prompt files for a particular project type, add it as a new eval case in evals/evals.json and use it to drive the fix.
MIT