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 crittylabs/critty --skill critty-ai-coworkgit clone --depth 1 https://github.com/crittylabs/crittyWrote 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/crittylabs/critty/critty-ai-cowork)<a href="https://agentmods.dev/skills/crittylabs/critty/critty-ai-cowork"><img src="https://agentmods.dev/badge/skills/crittylabs/critty/critty-ai-cowork/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/crittylabs/critty/critty-ai-cowork"><img src="https://agentmods.dev/badge/skills/crittylabs/critty/critty-ai-cowork.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00062 | $0.00655 |
| Opus 5.5 | $0.00025 | $0.00262 |
| Sonnet 5.5 | $0.00012 | $0.00131 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
critty-ai-cowork 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 yesterday.
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 — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cowork with Another AI
Experimental: interfaces and supported launch configurations may change.
Read critty-ai-review and follow its requester workflow, request identity, snapshot, posting, and completion contracts. This skill changes only how the requester acts between AI review rounds. Keep its reviewer role unchanged.
A request such as /critty-ai-cowork with Astra selects a collaborator for the current task and authorizes in-scope fixes and follow-up between agents. Follow the shared skill's with argument handling. Establish the target outcome and acceptance checks before dispatch, using existing task context. If the request only asks for an opinion, use critty-ai-review instead. Preserve the user's selected collaborator and the caller's execution permissions.
Replace the per-round checkpoint
After collecting and verifying each AI result:
- Assess the findings against the requirements and evidence. Exchange focused questions or counterexamples with the reviewer when needed; agreement alone is not evidence of correctness.
- Make authorized fixes and run the affected checks as the requester. The other AI reads, posts findings, replies to its own threads, and resolves its own verified findings through the restricted Critty interface; it does not edit files or execute checks.
- Capture the revised target and request review of the affected scope, explicitly carrying forward unresolved findings and permitting the reviewer to resolve its own findings after verification. Reuse valid results for unchanged content. Keep each assignment tied to its own version and completion report.
For a one-shot reviewer that has exited, continue an exchange by posting the requester's question or evidence as a reply, then launching a new assignment with a new request ID and references to that thread and the prior result. A live transport may continue on its existing handle. An exited process cannot receive another question merely by waiting on it.
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.
- yesterday First seen · 33 lines · 62 tokens per session scan A 08e74e073c63
critty-ai-cowork is a skill published in the GitHub repository crittylabs/critty (88 stars, last pushed yesterday), licensed MIT. It adds 62 tokens to every session and 655 once invoked, about $0.0002 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 2026-10-15.
Other skills, from other repositories
pr-comments
Fetch and display GitHub PR review comments for the current branch.
simplify
Clean up changed code while preserving intended behavior. Use when the user asks to simplify or improve code quality through reuse, simplification, efficiency, and abstraction reviews. Correctness bug hunting is outside scope.
cmd-review
Review the current diff or selected files (usage: /review [instructions | --last-diff | --target | --file | files...] [--style ]).
assess-patch-risk
Assess an immutable patch artifact's program impact, regression risk, and auto-merge eligibility. Use for generated patch files, provider pull-request diffs, or commit ranges when reviewers need evidence about affected runtime paths, contracts, tests, and recoverability. This skill is read-only and does not generate…
code-guidelines-go
Go 1.24–1.27 coding guidelines for the dimetron/pi-go AI agent runtime. Use this skill whenever writing, reviewing, or refactoring ANY Go code in pi-go. This covers idiomatic style, error handling, concurrency, project layout, testing (table-driven, fuzz, benchmarks, synctest), new stdlib usage, golangci-lint v2…
design-review
Deep design review of Go codebase — naming, structure, consistency, interfaces, error handling. Scores each dimension and provides actionable fixes.