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 UKGovernmentBEIS/inspect_evals --skill code-quality-review-allgit clone --depth 1 https://github.com/UKGovernmentBEIS/inspect_evalsWrote 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/code-quality-review-all)<a href="https://agentmods.dev/skills/ukgovernmentbeis/inspect_evals/code-quality-review-all"><img src="https://agentmods.dev/badge/skills/ukgovernmentbeis/inspect_evals/code-quality-review-all/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/code-quality-review-all"><img src="https://agentmods.dev/badge/skills/ukgovernmentbeis/inspect_evals/code-quality-review-all.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 | $0.00076 | $0.01358 |
| Opus 5.5 | $0.00030 | $0.00543 |
| Sonnet 5.5 | $0.00015 | $0.00272 |
| Haiku 4.5 | $0.00008 | $0.00136 |
Grade A, and why
code-quality-review-all 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review All Evaluations
Review all evaluations in the repository against a single code quality standard or topic. This workflow is useful for systematic code quality improvements and ensuring consistency across all evaluations.
Workflow
Setup
If not already provided, ask user for the topic from the CONTRIBUTING.md or BEST_PRACTICES.md that this review should be focused on. If not provided, come up with a short topic identifier in a file-safe format (e.g., pytest_marks, import_patterns, test_coverage).
Create or read existing directory structure:
<repo root>/agent_artefacts/code_quality/<topic_id>/- Directory for this review topic<repo root>/agent_artefacts/code_quality/<topic_id>/README.md- Documentation for this specific topic<repo root>/agent_artefacts/code_quality/<topic_id>/results.json- Results of the review<repo root>/agent_artefacts/code_quality/<topic_id>/SUMMARY.md- Summary of the review
README.md Structure
The README.md file should contain topic-specific information:
- Topic Description: What this review checks for and why it matters
- Requirements: Specific requirements from CONTRIBUTING.md or BEST_PRACTICES.md
- Detection Strategy: How to identify issues (patterns to look for, tools to use)
- Commands: Specific commands useful for this topic (grep patterns, pytest commands, etc.)
- Good Examples: Code snippets showing correct implementation
- Bad Examples: Code snippets showing common mistakes and how to fix them
- Review Date: When this documentation was created/updated
results.json Structure
The results.json file should follow the template in assets/results-template.json. It contains one entry per evaluation in <repo root>/src/inspect_evals/, with status and issue details.
Important: The issue_location field should use paths relative to the repository root with forward slashes (e.g., tests/foo/test_foo.py:42 or src/inspect_evals/foo/bar.py:15, not C:\Users\...\test_foo.py:42 or tests\foo\test_foo.py:42).
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.
- 1mo ago Changed b182339498f9
- 1mo ago Changed b415a048d7f1
- 2mo ago First seen · 126 lines · 76 tokens per session scan A acc7b50fda6c
code-quality-review-all is a skill published in the GitHub repository UKGovernmentBEIS/inspect_evals (721 stars, last pushed yesterday), licensed MIT. It adds 76 tokens to every session and 1,358 once invoked, about $0.0003 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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