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 eea/eea.agent.skills --skill code-qualitygit clone --depth 1 https://github.com/eea/eea.agent.skillsWrote 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/eea/eea.agent.skills/code-quality)<a href="https://agentmods.dev/skills/eea/eea.agent.skills/code-quality"><img src="https://agentmods.dev/badge/skills/eea/eea.agent.skills/code-quality/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/eea/eea.agent.skills/code-quality"><img src="https://agentmods.dev/badge/skills/eea/eea.agent.skills/code-quality.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 | $0.00040 | $0.03422 |
| Opus 5.5 | $0.00016 | $0.01369 |
| Sonnet 5.5 | $0.00008 | $0.00684 |
| Haiku 4.5 | $0.00004 | $0.00342 |
Grade A, and why
code-quality 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 — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Quality
Use this skill when code must be created correctly from the start, or when existing code must be repaired until it passes the repository's actual quality gates.
Primary goal
Make code pass the real checks that block delivery:
- repository formatters and linters
- type checks
- unit tests
- integration tests when present
- Docker-based test-image checks
- Jenkins stages generated for the repository
The skill is optimized for AI-generated code, where the preferred outcome is: generate correct code up front so no later fix-up pass is required.
When to use
Use this skill when you need to:
- implement new code that must pass CI on the first try
- repair code that already exists but fails lint, typing, or tests
- reduce manual
--fixcleanup after AI generation - align a repository with Jenkins quality gates
- decide which checks should auto-fix code and which should remain hard gates
Operating principles
- Treat the repository's real checks as the source of truth.
- Prefer prevention over cleanup: generate code that already matches project conventions.
- Separate safe auto-fixes from non-fixable policy rules.
- Do not assume one tool can fix everything.
- Do not declare success until the same commands used by Jenkins pass.
- Auto-fix before the commit, not in CI. Run the same safe-fixer commands
Jenkins'
Code lintingstage verifies (ruff check --fix,ruff format,black,isort,prettier --write, etc.) every time you add or modify code, before it gets committed. Jenkins can't commit fixes back, so if auto-fixable debt reaches CI, the pre-commit step was skipped; don't rely on a Jenkins-side auto-fix stage to catch it. Prefer running these natively on the host rather than through Docker when the installed tool versions matchDockerfile.test— see "Native tools vs Docker for pre-commit auto-fix" below. Don't skip the check just because it's usually fast; skipping it is exactly how auto-fixable debt reaches CI in the first place.
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 First seen · 330 lines · 40 tokens per session scan A 9ce60e286ce5
code-quality is a skill published in the GitHub repository eea/eea.agent.skills (5 stars, last pushed 20d ago), licensed MIT. It adds 40 tokens to every session and 3,422 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 2026-08-31.
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