by Priivacy-ai
Spec-Driven Development for serious software developers. Spec Coding with with Claude, Cursor, Gemini, Codex. Kanban dashboard, git worktrees, auto-merge and more.
# Add to your Claude Code skills
git clone https://github.com/Priivacy-ai/spec-kittyLast scanned: 4/30/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-04-30T06:28:17.412Z",
"semgrepRan": false,
"npmAuditRan": true,
"pipAuditRan": true
}spec-kitty is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Priivacy-ai. Spec-Driven Development for serious software developers. Spec Coding with with Claude, Cursor, Gemini, Codex. Kanban dashboard, git worktrees, auto-merge and more. It has 1,404 GitHub stars.
Yes. spec-kitty passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/Priivacy-ai/spec-kitty" and add it to your Claude Code skills directory (see the Installation section above).
spec-kitty is primarily written in Python. It is open-source under Priivacy-ai on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh spec-kitty against similar tools.
No comments yet. Be the first to share your thoughts!
Based on votes and bookmarks from developers who liked this skill
Spec Kitty is an open-source CLI for turning product intent into a repo-native AI coding workflow:
spec -> plan -> tasks -> next -> review -> accept -> merge
Use it to build a governed software factory around Claude Code, Codex, Cursor, Gemini, GitHub Copilot, Windsurf, OpenCode, and other AI coding agents. Spec Kitty keeps specs, plans, work packages, acceptance criteria, review state, and merge decisions in your repository, then gives agents isolated git worktrees so implementation can happen in parallel without branch chaos.
Spec Kitty is for teams building software factories: repeatable inputs, clear work-package boundaries, isolated execution, visible progress, and review gates. It can support dark software factories and autonomous coding experiments, but it is deliberately not a lights-out black box by default. Humans define intent, architecture, and acceptance criteria; agents implement inside traceable worktrees; reviewers accept, reject, or merge with an audit trail.
The goal is not more prompt text. The goal is a durable operating system for agentic coding where the repository remains the source of truth.
Use Spec Kitty when:
It is probably overkill for one-off edits, tiny scripts, or teams that do not use Git.
| Need | Spec Kitty provides |
|---|---|
| Start from intent | Guided specify, plan, and tasks workflows |
| Keep agents aligned | Repository-native mission artifacts under kitty-specs/ |
| Split implementation | Work packages with lifecycle lanes such as planned, in_progress, for_review, approved, and done |
| Run agents in parallel | Isolated git worktrees under .worktrees/ |
| Keep quality visible | Review, accept, merge, and retrospective gates |
| See progress | Optional local kanban dashboard with spec-kitty dashboard |
| Integrate agents | Slash commands or skills for Claude Code, Codex, Cursor, Gemini, Copilot, Windsurf, OpenCode, and more |
| Learn from missions | Every completed mission generates a retrospective by default. Tune via .kittify/config.yaml#retrospective or charter; see how-to. |
Spec Kitty keeps runtime governance in the repo instead of treating it as
agent-only prompt text. The trail model in docs/trail-model.md
describes how spec-kitty dispatch "<request>" maps operator intent to
runtime behavior, while
docs/host-surface-parity.md tracks parity across
CLI, slash-command, and hosted surfaces.
The primary standalone governance command is:
spec-kitty dispatch "<request>" - loads governance context, opens an Op record, and returns the context the agent must use before doing the workInstall the CLI:
pipx install spec-kitty-cli
pipx is the preferred installer for the CLI because it keeps Spec Kitty in its
own virtual environment and avoids the externally-managed-environment errors
common on modern Linux distributions.
Other supported install methods:
uv tool install spec-kitty-cli
# or, inside an activated virtual environment
python -m pip install spec-kitty-cli
Create or initialize a project:
spec-kitty init my-project --ai claude
cd my-project
spec-kitty verify-setup
Replace claude with your agent key when needed. Common choices include codex, cursor, gemini, copilot, opencode, qwen, windsurf, kiro, vibe, pi, and letta. See Supported Agents for the current list.
Open your AI coding agent in the project and run the core workflow:
/spec-kitty.charter
/spec-kitty.specify Build a small task list app.
/spec-kitty.plan
/spec-kitty.tasks
Then let the runtime choose the next action until the mission is ready:
spec-kitty next --agent claude --mission <mission-slug>
Review, accept, merge, and close the loop:
/spec-kitty.review
/spec-kitty.accept
/spec-kitty.merge --push
After merge, run /spec-kitty-mission-review. The mission's
retrospective.yaml is authored during the runtime terminus (HiC prompt or
autonomous facilitator), not by merge. Once it exists, use
spec-kitty retrospect summary for the cross-mission view and
spec-kitty agent retrospect synthesize --mission <mission-slug> to apply any
staged proposals (dry-run by default — pass --apply to mutate).
For the full walkthrough, see Your First Feature.
| Command | Purpose |
|---|---|
spec-kitty init . --ai <agent> |
Add Spec Kitty to the current repo |
spec-kitty verify-setup |
Check local installation and project wiring |
spec-kitty dashboard |
Open the local mission dashboard |
spec-kitty next --agent <agent> --mission <slug> |
Ask Spec Kitty what the agent should do next |
spec-kitty upgrade |
Update an existing project after upgrading the CLI |
spec-kitty --help |
Show available commands |
Start here:
Deeper topics:
Hosted auth, sync, and tracker flows remain opt-in. For setup details, see Hosted Sync Workspaces, Internal Hosted-Readiness, and Launch-Readiness Behavior.
Spec Kitty can be used as part of a dark software factory or autonomous coding pipeline, but its default model is governed and human-in-loop. It keeps specs, work packages, agent actions, review decisions, and merge state visible in the repository.
Spec Kitty supports common AI coding agents and coding harnesses including Claude Code, Codex, Cursor, Gemini, GitHub Copilot, OpenCode, Qwen, Windsurf, Kiro, Vibe, Pi, and Letta. See Supported Agents.
Spec Kitty is inspired by spec-driven development workflows, but adds repo-native mission state, work-package lanes, git worktree isolation, a local dashboard, governance commands, and an explicit next -> review -> accept -> merge runtime loop.
No. Spec Kitty is local-first and stores its core artifacts in your repo. Hosted tracker and sync integrations are optional.
git clone https://github.com/Priivacy-ai/spec-kitty.git
cd spec-kitty
pip install -e ".[test]"
When testing templates from a source checkout:
export SPEC_KITTY_TEMPLATE_ROOT="$(pwd)"
spec-kitty init my-project --ai claude
See the Contributing guide for contribution guidelines.
The drift-detector required check protects the shared identity-boundary
contract across Spec Kitty repos. Contributor and admin details live in
Identity-Boundary CI Gate.
Spec Kitty is released under the MIT License