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/vignesh2027/AI-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/vignesh2027/ai-agent-skills/review)<a href="https://agentmods.dev/commands/vignesh2027/ai-agent-skills/review"><img src="https://agentmods.dev/badge/commands/vignesh2027/ai-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/vignesh2027/ai-agent-skills/review"><img src="https://agentmods.dev/badge/commands/vignesh2027/ai-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 | $0.00000 | $0.00158 |
| Opus 5 | $0.00000 | $0.00079 |
| Sonnet 5 | $0.00000 | $0.00032 |
| Haiku 4.5 | $0.00000 | $0.00016 |
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 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.
What it actually says
Load agents/code-reviewer.md, skills/security-and-hardening/SKILL.md, and skills/performance-optimization/SKILL.md.
Conduct a thorough review of the code or PR described. Review all five dimensions:
- Correctness — Does it work correctly for all cases?
- Security — Are there vulnerabilities?
- Performance — Are there obvious inefficiencies?
- Readability — Is it clear and maintainable?
- Architecture — Does it fit the design?
For each issue: specify dimension, severity (Blocking/Major/Minor/Nit), location, what's wrong, why it matters, and a specific fix.
Do not approve code with Blocking issues. Blocking issues: security vulnerabilities, correctness failures, missing tests.
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 · 14 lines · 0 tokens per session scan A 3a29da0a0df5
review is a command published in the GitHub repository vignesh2027/AI-AGENT-SKILLS (2 stars, last pushed 11d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 158 tokens. 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 commands, from other repositories
review
Perform a thorough code review of: $ARGUMENTS.
sdd-init
Initialize SDD context — detects project stack and bootstraps persistence backend.
git
The pre-finish status: branch, hygiene findings, message checks, workflow lint, template state.
init
Install the formatters this repository needs, with every command visible before it runs.
refactor
Analyze code for SOLID violations and suggest targeted improvements.
review
Review the current diff against project memory.