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-bulk-edit-classificationgit 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-bulk-edit-classification)<a href="https://agentmods.dev/skills/priivacy-ai/spec-kitty/spec-kitty-bulk-edit-classification"><img src="https://agentmods.dev/badge/skills/priivacy-ai/spec-kitty/spec-kitty-bulk-edit-classification/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-bulk-edit-classification"><img src="https://agentmods.dev/badge/skills/priivacy-ai/spec-kitty/spec-kitty-bulk-edit-classification.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 283 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00157 | $0.03568 |
| Opus 5.5 | $0.00063 | $0.01427 |
| Sonnet 5.5 | $0.00031 | $0.00714 |
| Haiku 4.5 | $0.00016 | $0.00357 |
Grade A, and why
spec-kitty-bulk-edit-classification 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 1mo 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 — 359 lines — stays where its author put it; the contents beside it link to each section on GitHub.
spec-kitty-bulk-edit-classification
Drive the occurrence-classification guardrail (shipped in #393, DIRECTIVE_035) so users never have to know it exists. A bulk edit is any change that touches the same string in many places — a rename, a terminology migration, a package-path move, a feature-label swap. Those changes look mechanical but aren't: the same token carries different meaning depending on where it appears (code symbol, import path, filesystem literal, serialized key, CLI command, user-facing string, test fixture, log/telemetry label). Treating them uniformly is how silent breakage happens.
The user will not say "bulk edit". They will say "rename Coffee to Tea" or
"the Blue feature is now the Red feature." Your job is to recognize that
shape, turn on change_mode: bulk_edit, and drive the classification workflow
before any code changes.
When to activate
Apply this skill during specify or plan when the user's description matches any of these patterns:
| Pattern | Example phrasing |
|---|---|
| Explicit rename | "Rename Customer to Account across the codebase" |
| Terminology migration | "We're calling it 'channels' now, not 'streams'" |
| Feature relabel | "The Blue feature is now the Red feature" |
| Path/module move | "Move src/legacy/auth to src/auth" |
| API surface rename | "Rename the /users endpoint to /accounts" |
| Config key rename | "Change max_connections to connection_limit everywhere" |
| Brand / product rename | "Replace ACME with GlobalCorp in all docs and UI" |
Also apply when the implement or review command prints a message starting with "Bulk Edit Gate: BLOCKED" or "Bulk Edit Review: Diff Compliance" — these are the runtime gates' failure output; this skill tells you how to respond.
Do NOT apply when the user is:
- Adding a genuinely new feature (new identifiers, new files) — no existing identifiers change
- Refactoring the internals of one file or one function — no cross-cutting string change
- Fixing a bug where the surface names stay the same
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.
- 1mo ago Changed a28a15446fa4
- 2mo ago First seen · 359 lines · 157 tokens per session scan A a1aac566c8c3
spec-kitty-bulk-edit-classification is a skill published in the GitHub repository Priivacy-ai/spec-kitty (1,687 stars, last pushed 12d ago), licensed MIT. It adds 157 tokens to every session and 3,568 once invoked, about $0.0006 per session on Opus 5.5. 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.
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ears-spec-authoring
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