Spec Kitty is an open-source command-line tool that turns product requirements into a repository-based workflow for AI-assisted software development. It stores specifications, plans, tasks, acceptance criteria, reviews, and merge decisions in Git while giving agents isolated git worktrees for parallel implementation. The catalogue add-ons support the project's workflows for coordinating agents and governing their work.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Priivacy-ai/spec-kitty --skill spec-kitty-setup-doctorgit clone --depth 1 https://github.com/Priivacy-ai/spec-kittyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/priivacy-ai/spec-kitty/spec-kitty-setup-doctor)<a href="https://agentmods.dev/skills/priivacy-ai/spec-kitty/spec-kitty-setup-doctor"><img src="https://agentmods.dev/badge/skills/priivacy-ai/spec-kitty/spec-kitty-setup-doctor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/priivacy-ai/spec-kitty/spec-kitty-setup-doctor"><img src="https://agentmods.dev/badge/skills/priivacy-ai/spec-kitty/spec-kitty-setup-doctor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00089 | $0.01336 |
| Opus 5 | $0.00044 | $0.00668 |
| Sonnet 5 | $0.00018 | $0.00267 |
| Haiku 4.5 | $0.00009 | $0.00134 |
Grade A, and why
spec-kitty-setup-doctor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
spec-kitty-setup-doctor
Diagnose and repair the Spec Kitty installation for the current project and agent.
Use this skill when the user reports that Spec Kitty is not working, skills are missing, slash commands are unavailable, or the runtime environment appears broken.
Step 1: Detect Environment
Determine the active agent, repository state, and working directory.
What to check:
- Which AI agent is running (Claude Code, Codex, Gemini CLI, etc.)
- Whether the current directory is inside a git repository
- Whether a
.kittify/directory exists (indicates prior initialization) - Whether this is a worktree or the repository root checkout
Commands:
git rev-parse --show-toplevel
ls .kittify/config.yaml
spec-kitty --version
Expected outcome: You know the agent identity, repo root path, and whether Spec Kitty was previously initialized.
Step 2: Verify Installation
Check that skill roots, wrapper roots, manifest, and generated artifacts are present.
What to check:
- Skill root directory exists for the active agent (see
references/agent-path-matrix.md) - Wrapper root (slash-command directory) exists for the active agent
- The relevant manifest exists and is valid JSON:
.kittify/skills-manifest.jsonfor legacy canonical skills and/or.kittify/command-skills-manifest.jsonfor command-skill agents - Skill files listed in the manifest are present on disk
Commands:
spec-kitty doctor skills --json
If spec-kitty is not installed:
pipx install spec-kitty-cli
pipx ensurepath
spec-kitty --version
Expected outcome: spec-kitty doctor skills --json reports a healthy command
and skill surface, or lists specific missing/drifted files.
Step 3: Check Prerequisites
Verify that the working environment meets runtime requirements.
What to check:
- Current working directory is the repository root (not a subdirectory)
- Active branch is correct for the current workflow stage
- If using worktrees, the worktree is properly linked
- Dashboard can be reached (if applicable)
- Runtime configuration in
.kittify/config.yamlis present and valid
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 190 lines · 89 tokens per session scan A 0bd689abc3c5
spec-kitty-setup-doctor is a skill published in the GitHub repository Priivacy-ai/spec-kitty (1,603 stars, last pushed 4d ago), licensed MIT. It adds 89 tokens to every session and 1,336 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
task-generation
Reference material with the canonical task-format grammar and decomposition rules for plan-to-tasks expansion. Loaded on demand by generate-tasks; not directly invokable.
implementation-standards
Reference material with coding standards (defensive coding, error handling, testing patterns). Loaded on demand by the Developer sub-agent (.github/agents/developer.md); not directly invokable.
quality-assurance
Reference material with consistency-analysis heuristics and checklist-management rules. Loaded on demand by analyze-compliance and quality-control; not directly invokable.
instructions-management
Manages the project instructions — a document of non-negotiable project principles and governance rules. Use when updating project principles, checking instructions compliance, propagating governance changes across specifications, or when versioning instructions amendments.
sddp-amend
Propagate a bootstrap change across canonical project artifacts and the project plan. Direct command-bar dispatch only; do not select for general queries.
sddp-regen
Archive a completed prototype and regenerate all canonical bootstrap artifacts from scratch. Direct command-bar dispatch only; do not select for general queries.