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 helmedeiros/clean-code-skills --skill branch-reviewgit clone --depth 1 https://github.com/helmedeiros/clean-code-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/helmedeiros/clean-code-skills/branch-review)<a href="https://agentmods.dev/skills/helmedeiros/clean-code-skills/branch-review"><img src="https://agentmods.dev/badge/skills/helmedeiros/clean-code-skills/branch-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/helmedeiros/clean-code-skills/branch-review"><img src="https://agentmods.dev/badge/skills/helmedeiros/clean-code-skills/branch-review.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 | $0.00053 | $0.01343 |
| Opus 5 | $0.00026 | $0.00672 |
| Sonnet 5 | $0.00011 | $0.00269 |
| Haiku 4.5 | $0.00005 | $0.00134 |
Grade A, and why
branch-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 10d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Branch Code Quality Review
Compare old code on the base branch against new code on the feature branch and produce a detailed, evidence-backed scorecard across 11 quality dimensions.
When This Skill Applies
- The user wants to review the quality of changes on a feature branch
- Comparing old vs new implementation during a migration or rewrite
- The user asks for a scored code quality assessment
- Evaluating whether a branch is ready to merge
- Tracking quality progression across multiple review iterations
Core Principle
Measure code quality objectively by scoring 11 dimensions with real evidence — file names, line counts, pattern counts, and concrete examples. Honest, specific scores with improvement paths are more valuable than inflated ratings. Architecture, type safety, and testing are weighted more heavily because they compound over time.
Workflow
Step 1: Identify the Branch
Determine the feature branch and the base branch (main or master). If a branch name is provided, use it. Otherwise use the current branch.
Step 2: Gather Evidence
Run the following analyses against the diff between base and feature branch:
git diff <base>...HEAD --statto list all changed files.git diff <base>...HEADto read the actual changes.- Count lines per file. Flag files over 200 lines.
- Check type safety: strict mode,
@ts-ignore,@ts-expect-error,as any,as unknown,Record<string, any>. - Check styling approach: CSS modules vs inline styles (
style={{,style={). - Check test coverage: test files,
describe/it/testblocks, integration vs unit tests. - Check accessibility:
aria-attributes,role=, semantic HTML, color-only indicators. - Check error handling: try/catch, error boundaries, API error handling.
- Check code duplication: repeated constants, copy-pasted components, duplicated helpers.
- Check API integration: cancellation, retries, typed responses, caching.
- Check routing: lazy loading, nested layouts, 404 handling, breadcrumbs.
- Check state management: prop drilling depth, global state, custom hooks.
- Check DX tooling: linting, formatting, pre-commit hooks, import sorting.
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.
- 10d ago First seen · 98 lines · 53 tokens per session scan A 72f448fc3624
branch-review is a skill published in the GitHub repository helmedeiros/clean-code-skills (2 stars, last pushed 6mo ago), licensed MIT. It adds 53 tokens to every session and 1,343 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…
sip
After you create or change an artifact or skill, taste-test it with our own skills instead of trusting your in-session judgment — recursive self-improvement, made automatic. Use right after writing or editing anything, before calling it done, committing, or handing it off.
prism
Split one artifact — a claim, plan, or file — across 2 to 5 independent lenses, one per genuinely distinct failure mode (correctness, security, readability, cost, adversarial-user), and return their convergence: where they agree, where they disagree, and the single next question that resolves the disagreement. Use…
hate
Attack a plan, design, or argument like you want it to fail before you commit real effort — return the single load-bearing objection and the cheapest experiment that would prove it matters, not a checklist. User-invoked on purpose: a hate-it reflex always in the agent's reach would bias it toward demolition. Weighs…
issue-analyze
GitHub Issue and PR review thread deep analysis with Codex blind verdict. Use when: analyzing issue root cause, classifying problems, investigation planning, triaging PR review comments for actionability. Not for: fixing bugs (use bug-fix), code exploration (use code-explore). Output: classified analysis + verdict…
load-pr-review
Load GitHub PR review comments into AI session — analyze, triage, plan. Default: analysis-only (no auto-fix). Use when: reviewing PR feedback, planning fixes, addressing review comments, replying to reviewers. Not for: creating reviews (use codex-review-fast), creating PRs (use create-pr), viewing PR status (use…