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 jellydn/my-ai-tools --skill code-quality-reviewgit clone --depth 1 https://github.com/jellydn/my-ai-toolsWrote 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/jellydn/my-ai-tools/code-quality-review)<a href="https://agentmods.dev/skills/jellydn/my-ai-tools/code-quality-review"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/code-quality-review/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/jellydn/my-ai-tools/code-quality-review"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/code-quality-review.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 | $0.00026 | $0.02532 |
| Opus 5 | $0.00013 | $0.01266 |
| Sonnet 5 | $0.00005 | $0.00506 |
| Haiku 4.5 | $0.00003 | $0.00253 |
Grade A, and why
code-quality-review 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 9d 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Quality Review
Use this skill for an unusually strict review focused on implementation quality, maintainability, abstraction quality, and codebase health.
Above all, this skill should push the reviewer to be ambitious about code structure. Actively search for "code judo" moves: restructurings that preserve behavior while making the implementation dramatically simpler, smaller, more direct, and more elegant. Surface-level cleanup notes are useful but secondary — the real goal is structural simplification.
Core Prompt
Start from this baseline:
Perform a deep code quality audit of the current branch's changes. Rethink how to structure / implement the changes to meaningfully improve code quality without impacting behavior. Work to improve abstractions, modularity, reduce Spaghetti code, improve succinctness and legibility. Be ambitious, if there is a clear path to improving the implementation that involves restructuring some of the codebase, go for it. Be extremely thorough and rigorous. Measure twice, cut once.
Non-Negotiable Additional Standards
Apply the baseline prompt above, plus these explicit review rules:
-
Be ambitious about structural simplification.
- Push past surface feedback — "this could be a bit cleaner" is where the conversation starts, not where it ends.
- Look for opportunities to reframe the change so that whole branches, helpers, modes, conditionals, or layers disappear entirely.
- Prefer the solution that makes the code feel inevitable in hindsight.
- Assume there is often a "code judo" move available: a re-organization that uses the existing architecture more effectively and makes the change dramatically simpler and more elegant.
- When you see a path to delete complexity rather than rearrange it, push hard for that path.
-
Keep files under 1k lines. Treat crossing that boundary as a decomposition signal.
- When a PR would push a file past 1000 lines, that's a strong prompt to extract helpers, subcomponents, or modules before merging.
- Prefer decomposing: pull out helpers, split into focused modules, or introduce local abstractions.
- Waive this only when there is a compelling structural reason and the resulting file remains clearly organized.
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.
- 9d ago First seen · 196 lines · 26 tokens per session scan A ed96ca9dfd79
code-quality-review is a skill published in the GitHub repository jellydn/my-ai-tools (119 stars, last pushed 4d ago), licensed MIT. It adds 26 tokens to every session and 2,532 once invoked, about $0.0001 per session on Opus 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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