goldziher/ai-rulez

ai-rulez

A complete development workflow for AI coding tools

Documentation · Quick Start · Examples

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The Problem

Every AI coding tool wants its own config: Claude needs CLAUDE.md, Cursor wants .cursor/rules/, Copilot expects .github/copilot-instructions.md. Each has different formats, frontmatter, and directory conventions. If you use more than one tool, you’re maintaining duplicate rules that inevitably drift apart.

The Solution

Write your rules, context, skills, agents, and commands once in .ai-rulez/. Run generate. Get native configs for every tool you use.

npx ai-rulez@latest init && npx ai-rulez@latest generate

ai-rulez generates correct, tool-native output for 20 platforms: Claude, Cursor, Windsurf, Copilot, Gemini, Cline, Continue.dev, Codex, OpenCode, Hermes, Amp, Junie, Antigravity, and more. Each preset respects the target tool’s conventions — proper frontmatter, directory structure, file extensions, agent formats.

Generate Plugins, Not Just Config

ai-rulez doesn’t only write config into your repo — it also packages your project as distributable plugins. Run ai-rulez generate --plugin and the same .ai-rulez/ source (skills, commands, agents, MCP servers) becomes installable plugin bundles and a marketplace index for Claude, Cursor, Codex, Gemini, Kimi, OpenCode, Factory, and Hermes Agent.

ai-rulez generate --plugin           # write plugin bundles + marketplace.json
ai-rulez generate --plugin --dry-run # preview
ai-rulez verify --plugin             # prove committed output matches its sources

Write MCP launch commands and hooks once with the canonical ${PLUGIN_ROOT} variable; each runtime gets its own manifest with the variable and hook format rewritten to fit. Hermes generation emits both a project plugin and a buildable Python entry-point package. Use plugin.content_root to keep distributable skills separate from contributor governance. Supports single-plugin repos and monorepos ([marketplace].members), plus a Claude statusline passthrough. See Authoring Plugins.

What Ships Out of the Box

ai-rulez isn’t just a config generator. It ships with 33 builtin domains containing opinionated rules, agents, and workflows that establish a professional development baseline immediately.

Builtin Rules (auto-included)

These activate automatically. No configuration needed.

Builtin Agents

Specialized agents ready to use as subagents:

Opt-in Domains

Enable these based on your stack:

Languages (10): rust, python, typescript, go, java, ruby, php, elixir, csharp, r

Bindings (10): pyo3, napi-rs, magnus, ext-php-rs, rustler, wasm, jni-rs, extendr, cgo, vite-plus

Operational: cicd, docker, observability, documentation, polyglot-bindings, default-commands

# .ai-rulez/config.toml
builtins = ["rust", "python", "pyo3", "cicd", "docker", "default-commands"]

Language, binding, polyglot-bindings, and security (OWASP + dependency) conventions are emitted as on-demand Agent Skills (.claude/skills//SKILL.md) rather than inlined into CLAUDE.md, so the always-loaded file stays small and the conventions load only when relevant. Always-on rules (code-quality, testing, git-workflow, ai-governance, …) remain inline. !domain and !domain/name exclusions work for skill entries too.

Content Types

Organization at Scale

ai-rulez scales from solo projects to large organizations:

Domains — Group content by feature, language, or team:

.ai-rulez/domains/backend/rules/
.ai-rulez/domains/frontend/rules/

Profiles — Generate different configs for different audiences:

[profiles]
backend = ["backend", "database"]
frontend = ["frontend", "ui"]

Remote Includes — Share rules across repositories:

[[includes]]
name = "company-standards"
source = "https://github.com/company/ai-rules.git"
merge_strategy = "local-override"

Include sources can use a bare/flattened layout — expose rules/, context/, skills/, agents/ directly (at the repo root or a sub-path via path = "modules/core") with no .ai-rulez/ wrapper. Recommended for shared, skill-first modules.

Local overrides — Personal, machine-local instructions that never get committed:

ai-rulez add rule my-scratch-notes --local   # → .ai-rulez/local/rules/, generates CLAUDE.local.md

.ai-rulez/local/ and the generated *.local.md outputs are gitignored unconditionally. See docs/local-overrides.md.

Reasoning effort across providers — Tune how hard each AI tool thinks:

# .ai-rulez/agents/security-reviewer.md
---
name: security-reviewer
description: Reviews code for security regressions
effort: high
---

# .ai-rulez/config.toml
[defaults]
effort = "medium"  # global default for every supported preset

[defaults.effort_by_preset]
codex = "high"     # overrides the global default for Codex
claude = "xhigh"   # …and for Claude

Accepted values: low, medium, high, xhigh, max, inherit. ai-rulez emits the right field per preset:

• Claude — effort in .claude/agents/*.md frontmatter (per-agent)
• Codex — model_reasoning_effort in .codex/config.toml and .codex/agents/*.toml
• Amp — amp.anthropic.effort in .amp/settings.json (global)
• Windsurf — reasoning_effort in .windsurf/agents/*.md frontmatter (per-agent)
• Opencode — reasoningEffort in .opencode/agents/*.md frontmatter (per-agent)

Each preset maps the value to its own vocabulary; tools without a documented config surface (Cursor, Copilot, Gemini, etc.) are silently skipped. See docs/configuration.md for the full mapping table.

Per-preset model selection for subagents — Model strings differ per provider, so the same agent can declare a different model for each preset it targets:

# .ai-rulez/agents/research-helper.md
---
name: research-helper
description: Multi-provider research subagent
claude_model: opus
copilot_model: gpt-5
cursor_model: claude-3.7-sonnet
---

# .ai-rulez/config.toml — project-wide defaults
[defaults.model_by_preset]
claude = "sonnet"   # used when an agent doesn't set its own claude_model
copilot = "gpt-5"

Per-agent _model wins over defaults.model_by_preset; the legacy single model: field on an agent is the lowest-priority fallback for backward compatibility.

Installed Skills — Pull reusable skills from external repos:

[[installed_skills]]
name = "kreuzberg"
source = "https://github.com/kreuzberg-dev/kreuzberg"

MCP Server

ai-rulez includes a built-in MCP server with 35+ tools that lets AI assistants manage their own governance. Add rules, update context, generate configs — all programmatically.

[[mcp_servers]]
name = "ai-rulez"
command = "npx"
args = ["-y", "ai-rulez@latest", "mcp"]

Installation

No install needed — npx ai-rulez@latest works out of the box. Pick a permanent option below:

Documentation

Full documentation at goldziher.github.io/ai-rulez.

License

MIT