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/Amey-Thakur/AI-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/amey-thakur/ai-skills/review-my-code)<a href="https://agentmods.dev/commands/amey-thakur/ai-skills/review-my-code"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/review-my-code/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/amey-thakur/ai-skills/review-my-code"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/review-my-code.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 | $0.00019 | $0.00332 |
| Opus 5.5 | $0.00008 | $0.00133 |
| Sonnet 5.5 | $0.00004 | $0.00066 |
| Haiku 4.5 | $0.00002 | $0.00033 |
Grade A, and why
review-my-code 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.
What it actually says
You were invoked as a slash command. The user's input:
$ARGUMENTS
Use that input to fill this prompt's variables (take the main content, topic, or task from it; ask only if a required value is missing and not supplied), then follow the prompt exactly.
Review this code. Report only what you can defend with evidence from the code.
{code}
Context: {context}
Method:
- State in one sentence what the code is meant to do, so we agree on intent.
- Hunt in priority order: correctness (logic errors, off-by-one, null/error paths, race conditions), security (unvalidated input reaching queries, paths, or shell; secrets; missing authz), reliability (what happens when the input is empty, the call fails, two callers race), then maintainability (naming, duplication, dead code, missing tests).
- For each finding: file/line, the defect in one sentence, the concrete failing input or scenario, and a suggested fix.
- Rank by severity, worst first: Blocker, Major, Minor, Nit. Lead with the verdict ("N findings, worst is X").
Rules: verify before reporting (construct the failing case; if you cannot, ask it as a question, do not assert it). Do not flag style a formatter enforces. If the code is solid, say so plainly rather than inventing findings.
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 · 37 lines · 19 tokens per session scan A ba2792b2437d
review-my-code is a command published in the GitHub repository Amey-Thakur/AI-SKILLS (10 stars, last pushed 1mo ago), licensed MIT. It adds 19 tokens to every session and 332 once invoked, about $0.0001 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 2026-09-06.
Other commands, from other repositories
refactor-clean
Refactor provided code for cleanliness, maintainability, and alignment with SOLID principles and modern best practices — no over-engineering.
review-pr
Review a pull request against an authorized reviewer's brief — answer their questions, examine their angles, run their validations, and converse until they say done. Change NO code.
review-hard
Review the current task changes for correctness, safety, and maintainability risks before slice closure or PR prep, and recommend the smallest safe next step. Use when a slice or task-level implementation was completed, the user wants a focused engineering risk review before closure or PR prep, or meaningful issues…
apple-review
Full Apple-grade review (design + engineering + compliance + keynote). Review only, no fixes. Runs the apple-review skill.
code-simplify
Simplify code for clarity and maintainability — reduce complexity without changing behavior.
arc-audit
Audit a React Native Expo project for mobile UX issues, performance problems, and architecture violations. Use to check code quality against arc-skill best practices. Trigger when the user asks to review code, check for issues, wants a health check, mentions touch targets, accessibility, performance audit, or says 'is…