Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/UKGovernmentBEIS/inspect_evalsnpx agentmods add skills/ukgovernmentbeis/inspect_evals/ci-maintenance-workflowWrote 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/ukgovernmentbeis/inspect_evals/ci-maintenance-workflow)<a href="https://agentmods.dev/skills/ukgovernmentbeis/inspect_evals/ci-maintenance-workflow"><img src="https://agentmods.dev/badge/skills/ukgovernmentbeis/inspect_evals/ci-maintenance-workflow/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/ukgovernmentbeis/inspect_evals/ci-maintenance-workflow"><img src="https://agentmods.dev/badge/skills/ukgovernmentbeis/inspect_evals/ci-maintenance-workflow.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 | $0.00120 | $0.04704 |
| Opus 5.5 | $0.00048 | $0.01882 |
| Sonnet 5.5 | $0.00024 | $0.00941 |
| Haiku 4.5 | $0.00012 | $0.00470 |
Grade A, and why
ci-maintenance-workflow 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 24d 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 — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI Maintenance Workflows
This skill covers four CI/GitHub Actions-related workflows:
- Fix A Failing Test: Diagnose and fix a failing test from a CI run
- Fix A Failing Smoke Test: Diagnose and fix a failing smoke test (eval that fails with
--limit 0) - Mark Slow Tests: Add
@pytest.mark.slowmarkers to tests exceeding thresholds - Review PR: Automatically check a PR against agent-checkable standards
Write a PR For A Failing Test
This workflow is for fixing failing pytest tests (not smoke tests — see "Fix A Failing Smoke Test" below for those).
- The user should provide you with a link that looks like
https://github.com/ArcadiaImpact/inspect-evals-actions/actions/runs/<number>/job/<number2>, or a test to fix. If they haven't, please ask them for the URL of the failing Github action, or a test that should be fixed. - If a link is provided, you will be unable to view this link directly, but you can use 'gh run view' to see it.
- Checkout main and do a git pull. Make sure you're starting from a clean slate and not pulling in any changes from whatever you or the user was previously doing.
- Create a branch
agent/<number>for your changes, in inspect_evals. Note this is not the same as inspect-evals-actions where the above URL was from. - Identify the failing test(s) and any other problems. Verify the test currently fails in this environment by running it with
uv run pytest tests/<eval> --runslow. - Attempt these fixes one by one and verify they work locally, with
uv run pytest tests/<eval> --runslow. - On every change, assess if a task version bump and changelog entry are required. Read TASK_VERSIONING.md and PACKAGE_VERSIONING.md, then explicitly decide for this change. Default to bumping unless you can articulate why results remain comparable. Crash-fixes count: turning a sample that previously errored into one that now scores (correct or incorrect) changes which samples contribute to the aggregate, so the fix affects comparability even though no "scoring logic" was rewritten. If you bump, update the eval's README changelog and run
uv run scriv createfor a package-level fragment. - Perform linting as seen in .github/workflows/build.yml, and fix any problems that arise.
- Commit your changes to the branch.
- Before pushing, go over your changes and make sure all the changes that you have are high quality and that they are relevant to your finished solution. Remove any code that was used only for diagnosing the problem.
- Push your changes.
- Use the Github API to create a pull request with the change. Include a link to the failing test, which test failed, and how you fixed it. Include information on what you did to verify the fix worked. Always include the full checklist from
.github/PULL_REQUEST_TEMPLATE.mdverbatim in the PR body — theCheck PR templateCI job greps for the literal checklist substrings and fails the PR otherwise. This applies to bot/automated PRs too.
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.
- 24d ago Changed 98b9659ffb94
- 1mo ago Changed · +8 lines b39d4305047e
- 2mo ago First seen · 294 lines · 120 tokens per session scan A f60d8b2e2aac
ci-maintenance-workflow is a skill published in the GitHub repository UKGovernmentBEIS/inspect_evals (721 stars, last pushed yesterday), licensed MIT. It adds 120 tokens to every session and 4,704 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 2026-08-30.
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