Borrowing it
Nothing to install: this file belongs to justomsharma/github-resume-assistant. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/justomsharma/github-resume-assistant/main/.claude/skills/self-review/SKILL.mdgit clone --depth 1 https://github.com/justomsharma/github-resume-assistantWrote 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/justomsharma/github-resume-assistant/self-review)<a href="https://agentmods.dev/skills/justomsharma/github-resume-assistant/self-review"><img src="https://agentmods.dev/badge/skills/justomsharma/github-resume-assistant/self-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/justomsharma/github-resume-assistant/self-review"><img src="https://agentmods.dev/badge/skills/justomsharma/github-resume-assistant/self-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 | $0.00046 | $0.00365 |
| Opus 5.5 | $0.00018 | $0.00146 |
| Sonnet 5.5 | $0.00009 | $0.00073 |
| Haiku 4.5 | $0.00005 | $0.00036 |
Grade A, and why
self-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 2mo 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.
What it actually says
self-review
Review the working diff like a skeptical reviewer who did NOT write it. This is the last check before committing.
Look at the actual diff
git status
git diff
Review checklist (in order)
- Correctness — Does it do what was intended? Trace the logic. Any off-by-one, null case, or missed branch? Especially: the empty-GitHub path.
- Secrets — Scan every changed line. No
GITHUB_TOKEN,ANTHROPIC_API_KEY, or any key/credential..envmust not be staged. - Scope — Only the intended files changed? No stray edits, no scope creep
beyond the approved
/plan-firstapproach or the ROADMAP item? - Practices (CODING_PRACTICES.md) — Types present? Error handling on external
calls?
core/free of MCP imports? No bareexcept, no dead code, no debug prints? - Tests (TESTING.md) — Are the changes actually covered? External calls mocked?
Outcome
- If issues found: fix them now (or return to
/implement//plan-firstif the problem is deeper), then re-review. - If clean: summarize what changed in 2–3 lines for the commit/PR.
Handoff
Once the diff is clean → hand off to /commit-push.
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.
- 2mo ago First seen · 39 lines · 46 tokens per session scan A dad61e96e75b
self-review is a skill published in the GitHub repository justomsharma/github-resume-assistant (0 stars, last pushed 3mo ago), licensed MIT. It adds 46 tokens to every session and 365 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.
Other skills, from other repositories
quick-review
Review a code diff or file for correctness bugs, security issues, and clear simplifications. One finding per line, severity-tagged. Use when user wants fast, focused code review.
code
Use BEFORE generating, refactoring, reviewing, or debugging code. Trigger phrases include "write a function/script/class for X", "review this code/diff/PR", "refactor this", "debug this error", "is this implementation correct", "what's wrong with this code", "improve this code", "translate from X to Y", or any prompt…
pr-comment-formatter
Formats aggregated reviewer findings into a single structured PR comment with collapsed sections per checker, severity icons, and a top summary. Use when aggregating security, performance, or test findings for a PR, or when the orchestrator assembles a final report. Does NOT fetch diffs or call the GitHub API — that…
merge-batch
Prepare and merge an owner-selected PR batch with contributor credit and exact-candidate admission. Use for a pasted PR list; combined focused validation is diagnostic, and every actual landing still requires its applicable checks and authorization.
make-pr-easy-to-review
Prepare PRs for review by cleaning noisy history, improving PR descriptions, and adding reviewer guidance without changing code behavior. Use for "make this easy to review", "tidy this PR", "clean up commits", or "annotate the diff".
review-work
Post-implementation gate review: run manual QA on the real surface yourself, then launch ONE gate reviewer (never a panel) to audit goal, constraints, code quality, security, missed context, and QA evidence. Use before a PR handoff or when the user explicitly asks to review completed work.