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.
git clone --depth 1 https://github.com/ishandutta2007/Awesome-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/commands/ishandutta2007/awesome-agent-skills/review)<a href="https://agentmods.dev/commands/ishandutta2007/awesome-agent-skills/review"><img src="https://agentmods.dev/badge/commands/ishandutta2007/awesome-agent-skills/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/commands/ishandutta2007/awesome-agent-skills/review"><img src="https://agentmods.dev/badge/commands/ishandutta2007/awesome-agent-skills/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 | $0.00016 | $0.00178 |
| Opus 5 | $0.00008 | $0.00089 |
| Sonnet 5 | $0.00003 | $0.00036 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
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 12d 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.
This is a copy
100% identical to review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Invoke the agent-skills:code-review-and-quality skill.
Review the current changes (staged or recent commits) across all five axes:
- Correctness — Does it match the spec? Edge cases handled? Tests adequate?
- Readability — Clear names? Straightforward logic? Well-organized?
- Architecture — Follows existing patterns? Clean boundaries? Right abstraction level?
- Security — Input validated? Secrets safe? Auth checked? (Use security-and-hardening skill)
- Performance — No N+1 queries? No unbounded ops? (Use performance-optimization skill)
Categorize findings as Critical, Important, or Suggestion. Output a structured review with specific file:line references and fix recommendations.
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.
- 12d ago First seen · 17 lines · 16 tokens per session scan A 8ad7da75873b
review is a command published in the GitHub repository ishandutta2007/Awesome-Agent-Skills (21 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 178 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to review, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
final-review
Command "final-review" from adriannoes/awesome-agentic-ai, covering final review - comprehensive pr review & testing, step 0: determine review pass, step 1: create or update the pr, step 2: launch three review agents in parallel and agent 1: codebase consistency reviewer.
code-review
Perform a thorough code review that verifies functionality, maintainability, and security before approving a change. Focus on architecture, readability, performance implications, and provide actionable suggestions for improvement.
code-review
Code review — local uncommitted changes or GitHub PR (pass PR number/URL for PR mode).
quality
Independent quality auditor. --gate blocks a ck:cook phase on architecture/ownership/maintainability findings. --audit , --diff , or --changed audit any target standalone (report-only unless --save). --verify re-checks prior findings. Never edits code or writes tests.
review
/review — Request code review.
deslop
Source: hamzafer/cursor-commands (MIT).