agent-onboarding
Make your repository AI-ready with single skill run
What it does
Purpose
Initialize a repository so that AI coding agents (Claude Code, Codex, Cursor, etc.) can operate safely, deterministically, and with minimal human supervision.
This skill generates:
- AGENTS.md (agent operational contract)
- docs/ directory with structured technical documentation
Inputs
- Repository to initialize.
- Optional: short human note describing the project and instructions (1–3 sentences)
Outputs
- AGENTS.md at repository root
- docs/ directory with standardized markdown files
Core Principles
- Do NOT guess. If information is missing, explicitly mark TODOs.
- Prefer correctness and safety over completeness.
- Optimize for agent execution, not human prose.
- Minimize exploration cost and failure modes.
- If the given repository follows a monorepo pattern, create a subdirectory under docs/ for each project so the documentation doesn’t get mixed together.
- Example)
docs/frontend/00_overview.mddocs/frontend/adrdocs/frontend/plan
- Example)
Execution Steps
Step 1: Repository Inspection
- Detect:
- Primary language(s)
- Framework(s)
- Package manager
- Test framework
- Deployment indicators (Dockerfile, CI configs, Vercel, etc.)
- Identify:
- Entry points
- Core business logic directories
- Infrastructure-related files (DB, queues, storage)
If detection is ambiguous:
- Record ambiguity explicitly in docs/00_overview.md
- Do NOT assume defaults
Step 2: Confirm Ambiguities & Decisions With the Human
Request the user to provide the following information:
- Whether Git-related commands are allowed: use freely vs use only with explicit approval
- Language preferences:
- Language for comments, documents and commit messages
- Communication language: same as the user vs a specific language
- Any other items discovered in Step 1 that are ambiguous or seem to require questions
If the human does not answer:
- Do NOT guess.
- Pause and ask again as needed; if you must proceed, mark missing items as “Unknown / TODO” in docs (without embedding the unanswered questions), and keep AGENTS.md conservative (minimal privileges, no destructive ops).
Step 3: Generate AGENTS.md
First, copy AGENTS.md.example, then edit it based on the information gathered so far to create AGENTS.md.
AGENTS.md MUST include:
Repository Guidelines
Project Structure & Module Organization
Documentation
Coding Style & Naming Conventions
Commit Message & PR Guidelines
Commit Message Format
Atomic Commits
Agent Operation & Safety Rules
Language Policy
User Interaction
Hard rules:
- Keep AGENTS.md concise (target: 50–120 lines)
- Link to docs/ instead of duplicating explanations
Step 4: Generate docs/ Structure
If the docs/ directory already exists, generate all new files inside docs/agents/ instead of docs/. Otherwise, use docs/ as the target directory.
Create the following files if applicable:
- docs/00_overview.md
- docs/10_architecture.md
- docs/20_dev_env.md
- docs/30_commands.md
- docs/40_testing.md
- docs/50_deploy.md
- docs/60_observability.md
- docs/70_security.md
- docs/80_style_guide.md
- docs/90_troubleshooting.md
Rules:
- Omit files that are clearly irrelevant
- Never fabricate cloud providers, CI tools, or databases
- Prefer explicit “Unknown / TODO” over assumptions
Step 5: ADR Detection (Optional but Recommended)
If architectural decisions are inferred:
- Create docs/adr/
- Record assumptions as provisional ADRs
- Mark them as “UNVERIFIED”
Step 6: Validation Checklist
Before finalizing:
- All commands copy-paste runnable OR marked TODO
- No secrets included
- No speculative tech choices
- AGENTS.md links resolve correctly
Failure Handling
If the repository is:
- Empty
- Too small to infer structure
- Highly ambiguous
Then:
- Generate minimal AGENTS.md
- Generate docs/00_overview.md that clearly separates detected facts vs “Unknown / TODO” items (but do not include a question list; ask any needed questions during execution).
If, at any point, you encounter ambiguities or actions that appear potentially risky:
Then:
- always pause and request clarification from the user before proceeding.
Non-Goals
- Do not optimize for marketing or onboarding humans
- Do not refactor code
- Do not introduce new dependencies
- Do not modify runtime behavior
Success Criteria
A coding agent can:
- Identify where to make changes
- Execute tests confidently
- Avoid destructive or unsafe operations
- Complete scoped tasks without human correction
Capabilities
Install
Quality
deterministic score 0.45 from registry signals: · indexed on github topic:agent-skills · 9 github stars · SKILL.md body (4,763 chars)