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 Cratis/AI --skill cratis-engineering-regression-clustergit clone --depth 1 https://github.com/Cratis/AIWrote 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/cratis/ai/cratis-engineering-regression-cluster)<a href="https://agentmods.dev/skills/cratis/ai/cratis-engineering-regression-cluster"><img src="https://agentmods.dev/badge/skills/cratis/ai/cratis-engineering-regression-cluster/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/cratis/ai/cratis-engineering-regression-cluster"><img src="https://agentmods.dev/badge/skills/cratis/ai/cratis-engineering-regression-cluster.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 | $0.00137 | $0.00949 |
| Opus 5.5 | $0.00055 | $0.00380 |
| Sonnet 5.5 | $0.00027 | $0.00190 |
| Haiku 4.5 | $0.00014 | $0.00095 |
Grade A, and why
cratis-engineering-regression-cluster 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 2d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The third issue on one surface names a failure class
Each bug fixed alone adds one specification for one symptom. When the same surface (one screen, endpoint, command, query, workflow, module or rule area) breaks a third time, the instances share a cause that no specification owns yet, and the fourth instance is already on its way. Stop fixing instances: name the failure class, give it an owning gate, then fix the instance.
Count first
Before fixing an issue, count the earlier ones on its surface:
gh issue list --state all --search "<surface> in:title,body" --limit 50
git log --oneline -- <paths of the surface>
Count bugs, regressions, reverts and review findings, open or closed. Fewer than three: fix the instance with a regression specification. Three or more: follow the steps below before writing the fix.
Steps
- Name the failure class in one sentence that states the property being violated, not the symptom. Each earlier issue must be an instance of it, and a reader must be able to recognize the next one by it. "Owner filter shows archived items" is a symptom; "list filters are not exercised through the rendered list by any test" is a class.
- Choose the owning gate by enforcement kind, preferring the earliest that can catch the class: an analyzer (compile time), a lint rule, a CI check or verification script, or one specification suite that covers every member of the class (every filter, every endpoint), not one specification per bug. A class that only judgment can catch gets a review checklist entry, and the choice is stated as judgment-shaped; see the enforcement rule in authoring-skills.md.
- Prove the gate fails on the current broken instance, or on the earlier instances with their fixes reverted, before fixing anything. A gate that passes on the broken code owns nothing; follow guards-and-fuses.md so it cannot pass vacuously.
- Register the class. When the repository keeps a failure-class table or gate inventory, add one row: class, owning gate, where it runs. Otherwise put the class name in the gate's failure message and the specification or check name, so the next failure names its class.
- Fix the instance; the gate turns green. Run it with the repository's normal gates, and make it a required CI check when it lives in CI.
- Close the loop. Link the earlier issues to the class in the pull request comment, and leave a prose rule only for the judgment-shaped part.
What ships with it
1 file 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.
- 2d ago First seen · 74 lines · 137 tokens per session scan A 7f5ce1c65bc9
cratis-engineering-regression-cluster is a skill published in the GitHub repository Cratis/AI (4 stars, last pushed yesterday), licensed MIT. It adds 137 tokens to every session and 949 once invoked, about $0.0005 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 2026-10-19.
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