init
Creates, updates, or optimizes an AGENTS.md file for a repository with minimal, high-signal instructions covering non-discoverable coding conventions, tooling quirks, workflow preferences, and project-specific rules that agents cannot infer from reading the codebase. Use when setting up agent instructions or Claude configuration for a new repository, when an existing AGENTS.md is too long, generic, or stale, when agents repeatedly make avoidable mistakes, or when repository workflows have changed and the agent configuration needs pruning. Applies a discoverability filter—omitting anything Claude can learn from README, code, config, or directory structure—and a quality gate to verify each line remains accurate and operationally significant.
Best use case
init is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Creates, updates, or optimizes an AGENTS.md file for a repository with minimal, high-signal instructions covering non-discoverable coding conventions, tooling quirks, workflow preferences, and project-specific rules that agents cannot infer from reading the codebase. Use when setting up agent instructions or Claude configuration for a new repository, when an existing AGENTS.md is too long, generic, or stale, when agents repeatedly make avoidable mistakes, or when repository workflows have changed and the agent configuration needs pruning. Applies a discoverability filter—omitting anything Claude can learn from README, code, config, or directory structure—and a quality gate to verify each line remains accurate and operationally significant.
Teams using init should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/init/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How init Compares
| Feature / Agent | init | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Creates, updates, or optimizes an AGENTS.md file for a repository with minimal, high-signal instructions covering non-discoverable coding conventions, tooling quirks, workflow preferences, and project-specific rules that agents cannot infer from reading the codebase. Use when setting up agent instructions or Claude configuration for a new repository, when an existing AGENTS.md is too long, generic, or stale, when agents repeatedly make avoidable mistakes, or when repository workflows have changed and the agent configuration needs pruning. Applies a discoverability filter—omitting anything Claude can learn from README, code, config, or directory structure—and a quality gate to verify each line remains accurate and operationally significant.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
## When to use Use this skill when creating or updating `AGENTS.md` for a repository. Use it especially when: - the current `AGENTS.md` is long, generic, or stale - agents repeatedly make the same avoidable mistakes - repository workflows changed and agent guidance needs pruning ## Instructions Treat `AGENTS.md` as a **living list of non-discoverable landmines and workflow gotchas**, not a codebase overview. ### Core rule: discoverability filter Before adding any line, ask: > Can an agent discover this by reading the repo (`README`, code, config, scripts, directory tree)? - If **yes**: do **not** include it in `AGENTS.md`. - If **no**, and it materially affects task success/cost/safety: include it. ### What earns a line Include only guidance that is: 1. **Non-discoverable** from repository files alone 2. **Operationally significant** (changes commands, outcomes, or safety) 3. **Actionable** (specific enough to execute) Typical examples: - Non-standard tooling choices (e.g. use `uv` instead of `pip`) - Command caveats (e.g. tests must run with `--no-cache` due to fixture behavior) - Hidden constraints/landmines (deprecated directories still imported in production) - Critical local conventions that are not encoded in lint/tests/config ### What to remove or avoid Do **not** include: - Tech stack summaries - Directory structure overviews - Architecture descriptions agents can infer from code - Generic best-practice advice - Rules already enforced by tooling (linters, typecheck, tests, CI) - Mandatory boilerplate headers unless the repo explicitly requires one ### Recommended structure Prefer short, high-signal sections such as: - `Scope & routing` (which areas need separate/module-local AGENTS files) - `Non-discoverable commands` - `Landmines / do-not-touch areas` - `Task-specific constraints` For large repos, recommend **hierarchical AGENTS.md** files near relevant modules instead of one monolithic root file. ### Source files to check first - Existing `AGENTS.md` - `README.md` - `PROJECT.md` (if present) - Cursor rules (`.cursor/rules/` or `.cursorrules`) - Copilot instructions (`.github/copilot-instructions.md`) - `GEMINI.md` - CI/workflow files and package manager config (for command/tooling mismatches) If `AGENTS.md` exists, improve it incrementally instead of replacing it blindly. ### Maintenance mindset `AGENTS.md` is temporary guidance, not permanent configuration. When recurring issues appear: 1. Prefer fixing the root cause in code/tooling (lint rule, test, script, structure) 2. Keep only the minimum instruction needed until the root cause is solved 3. Prune stale instructions aggressively ### Quality gate before finalizing For each line in `AGENTS.md`, verify: - Is it non-discoverable? - Is it still accurate today? - Does it materially reduce mistakes/cost/time? Delete any line that fails one of these checks.
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