By hatch3r
Orchestrate agentic coding workflows across multiple AI coding tools from a single canonical source — define agents, skills, rules, commands, and hooks that enforce quality gates for security, testing, accessibility, maintainability, and observability throughout development, review, and release.
Run a known-cause bug fix through a 3-phase test-first pipeline -- reproduce + root-cause, regression-test + fix together, then root-cause-depth review -- with full sub-agent delegation.
Diagnose a complex incident -- reproduce the symptom, rank root-cause hypotheses, design the fix path, and emit regression coverage items as a board-ready investigation
Reverse-engineer a brownfield codebase into current-state module boundaries, integration-point inventory, tech-debt register, and dependency graph via static analysis
Author a custom user-tier artifact (agent, skill, rule, command, or hook) for this project. Generates frontmatter and body skeleton, applies strict + gentle quality gates, writes to .hatch3r/overrides/{type}/, and offers to sync to all enabled adapters.
Standalone debug-and-fix workflow — add strategic debug logging, collect runtime logs from the user, perform root cause analysis, implement the fix, and clean up all debug artifacts.
System architect who designs architecture, creates ADRs, analyzes dependencies, designs APIs and database schemas, and evaluates architectural trade-offs. Use when making architectural decisions, designing new systems, or evaluating design trade-offs.
Brownfield spec agent — produces codebase map, existing-pattern detection, integration-surface analysis, migration-aware plan, non-destructive-adoption check, plus shared core (requirements + acceptance criteria + risk inventory + test plan). Use when adding to or migrating an existing codebase.
CI/CD specialist who monitors CI pipeline runs, diagnoses failures, and suggests fixes. Use when CI fails, when waiting for CI results, or when investigating flaky tests.
Context-aware rules engine that applies coding standards based on file type, location, and project conventions. Use when enforcing project rules on save or reviewing files against established patterns.
Authors user-tier custom artifacts (agents, skills, rules, commands, hooks) under .hatch3r/overrides/. Validates frontmatter schema, runs strict + gentle quality gates, and writes the artifact only when all strict gates pass.
Ongoing backlog refinement for existing board items. Re-prioritize, reclassify, re-scope, archive stale items, decompose oversized issues, merge duplicates, refresh dependencies, and remediate board health findings.
Initializes a project board (GitHub Projects V2, Azure Boards, or GitLab Issue Boards) with hatch3r's label taxonomy, status fields, and board structure. Platform detected from hatch.json.
Regenerates the living board overview dashboard from current board state. Scans all open issues, computes health metrics, and updates the meta:board-overview issue.
Shared context and procedures for all board commands. Provides platform-agnostic board config, label taxonomy, branch conventions, sync enforcement, and tooling directives. Platform-specific details are in commands/board/shared-{platform}.md.
Opt-in browser verification skill — Playwright-driven visual checks, axe-core a11y audits, screenshot regression diffs, and E2E test scaffolds. Default ON for UI-affecting agent invocations; disable globally via hatch3r config browser=off.
Uses power tools
Uses Bash, Write, or Edit tools
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Crack the egg. Hatch better agents.
hatch3r is an open-source CLI and editor plugin (Claude Code + Cursor) that installs a tool-agnostic agentic coding setup into any repository. Audited each release across 24 governance domains and generated for 3 platform adapters (Claude Code, Cursor, GitHub Copilot). One command gives you the full set of agents, skills, rules, commands, hooks, and MCP integrations -- optimized for your coding tool of choice (live counts in governance/inventory.json ). Selective init installs only what you need based on your project type and team size.
v1.9.0 scope cut: As of 1.9.0 hatch3r supports only Claude Code, Cursor, and GitHub Copilot. Twelve adapters were removed in a hard cut; canonical content is now read from the bundled npm package (no
.agents/materialization in user repos), and the manifest moved to.hatch3r/hatch.json. See CHANGELOG.md for the full breaking-change list and migration notes.
Requires Node.js 22+.
npx hatch3r init --default # recommended: zero-prompt setup with the standard profile
npx hatch3r init # interactive: customize profile, tools, and CLI tools (6 prompts for GitHub greenfield; +1 for Azure DevOps, +1 for `custom` preset, +1 for workspace mode)
--default generates a working standard-profile setup with no questions — the fastest path to a configured repo. The interactive init detects your repo, infers your project context (greenfield/brownfield, solo/team), then walks platform → repo identity → content profile (minimal/standard/full/custom) → tools → CLI-tools picker, and generates everything. MCP is not prompted — opt in with --mcp or npx hatch3r mcp setup later. The platform (GitHub, Azure DevOps, or GitLab) is auto-detected from your git remote either way. Run into issues? See Troubleshooting.
Already using Cursor? Carry your existing rules across with npx hatch3r init --import cursor — they land under .hatch3r/overrides/rules/ (.md + .mdc) with per-file conflict reporting. See Migrating from another tool.
| Category | Count | Highlights |
|---|---|---|
| Agents | 29 | Code reviewer, lint-fixer, dependency auditor, implementer (sub-agentic), fixer, researcher, architect, DevOps, handoff loader / preparer, 9 content-quality specialists (UI/UX/security/reliability/testability/scalability/performance/maintainability/enhancability), and more |
| Skills | 53 | Bug fix, feature implementation, issue workflow, release, incident response, context health, cost tracking, handoff prepare / resume, recipes, API spec, CI pipeline, migration, customization, board lifecycle, ad-hoc orchestration scaffold, 5 standalone CLI-tool skills (ripgrep, jq, gh, fd, fzf) + a 24-tool cli-toolbox, and more |
| Rules | 67 | Code standards, testing, API design, observability, theming, i18n, security patterns, agent orchestration, fan-out discipline, right-sizing, deep context analysis, handoff readiness, mobile + backend stack rules, and more |
| Commands | 30 | Board management, planning (feature, bug, refactor, test), workflow, quick-change, bug-pipeline, revision, debug, healthcheck, security-audit, onboard, benchmark, handoff (prepare/resume/list/complete/prune), and more |
| CLI tools | 29 across 3 tiers | Tier-1 default (ripgrep, fd, jq, yq, gh, delta, bat, sd, ast-grep, zstd); tier-2 conditional (Playwright, duckdb, qsv, taplo, glab, az-devops, Docker, llm, fzf, lazygit, difftastic); tier-3 opt-in (RTK, Stagehand, aichat, mods, Comby, miller, csvkit, Podman) -- emitted as per-tool canonical skills + a decision-tree overview |
| MCP Servers | 10 (opt-in) | Playwright, Context7, Filesystem, GitHub, Brave Search, Sentry, Postgres, Linear, Azure DevOps, GitLab -- pure opt-in since 2.0.0: init --mcp or npx hatch3r mcp setup (interactive init does not prompt for MCP; features.mcp defaults to false) |
| Platforms | 3 | GitHub, Azure DevOps, GitLab -- auto-detected from git remote |
| Tool | Output |
|---|---|
| Cursor | .mdc rules, agents, skills, commands, MCP config |
| GitHub Copilot | instructions, prompts, GitHub agents |
| Claude Code | CLAUDE.md, skills, .mcp.json |
Platform is auto-detected from your git remote during hatch3r init. All board commands, agents, rules, and skills adapt to your selected platform.
npx claudepluginhub hatch3r/hatch3r --plugin hatch3rComplete project development toolkit: 23 agents, 23 slash commands, 29 lifecycle hooks, and 69 reusable skills for Claude Code workflows
Makes a repo agent-ready: AGENTS.md, boundary tests, CI pipeline, GC scripts — based on OpenAI's harness engineering methodology
Harness for Claude Code — skills, /harness:* slash commands, persona subagents, lifecycle hooks, and MCP tools without per-repo `harness setup`. Sibling plugins exist for Cursor, Gemini CLI, and Codex.
Analyze and enforce best practices for AI coding agent projects. Assess codebase readiness across 8 pillars with /readiness, then scaffold enforcement with /setup: TDD, secret scanning, file size limits, auto-generated docs, and git hooks.
Skills, hooks, templates, and engineering guides for bootstrapping AI-agent-friendly projects, with a per-project self-improvement loop.
Task-focused agents for test, review, debug, docs, CI, security, refactoring, research, performance, and search-replace — with teammate and subagent role guidance