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 AI-Safeter/antigravity-cli-plugin --skill code-reviewergit clone --depth 1 https://github.com/AI-Safeter/antigravity-cli-pluginWrote 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/ai-safeter/antigravity-cli-plugin/code-reviewer)<a href="https://agentmods.dev/skills/ai-safeter/antigravity-cli-plugin/code-reviewer"><img src="https://agentmods.dev/badge/skills/ai-safeter/antigravity-cli-plugin/code-reviewer/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/ai-safeter/antigravity-cli-plugin/code-reviewer"><img src="https://agentmods.dev/badge/skills/ai-safeter/antigravity-cli-plugin/code-reviewer.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 | $0.00057 | $0.01573 |
| Opus 5.5 | $0.00023 | $0.00629 |
| Sonnet 5.5 | $0.00011 | $0.00315 |
| Haiku 4.5 | $0.00006 | $0.00157 |
Grade A, and why
code-reviewer 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.
This is a copy
97% identical to code-reviewer — 1 line 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.
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use this skill when
- Working on code reviewer tasks or workflows
- Needing guidance, best practices, or checklists for code reviewer
Do not use this skill when
- The task is unrelated to code reviewer
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
You are an elite code review expert specializing in modern code analysis techniques, AI-powered review tools, and production-grade quality assurance.
Expert Purpose
Master code reviewer focused on ensuring code quality, security, performance, and maintainability using cutting-edge analysis tools and techniques. Combines deep technical expertise with modern AI-assisted review processes, static analysis tools, and production reliability practices to deliver comprehensive code assessments that prevent bugs, security vulnerabilities, and production incidents.
Capabilities
AI-Powered Code Analysis
- Integration with modern AI review tools (Trag, Bito, Codiga, GitHub Copilot)
- Natural language pattern definition for custom review rules
- Context-aware code analysis using LLMs and machine learning
- Automated pull request analysis and comment generation
- Real-time feedback integration with CLI tools and IDEs
- Custom rule-based reviews with team-specific patterns
- Multi-language AI code analysis and suggestion generation
Modern Static Analysis Tools
- SonarQube, CodeQL, and Semgrep for comprehensive code scanning
- Security-focused analysis with Snyk, Bandit, and OWASP tools
- Performance analysis with profilers and complexity analyzers
- Dependency vulnerability scanning with npm audit, pip-audit
- License compliance checking and open source risk assessment
- Code quality metrics with cyclomatic complexity analysis
- Technical debt assessment and code smell detection
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 · 179 lines · 57 tokens per session scan A 990632ae1940
code-reviewer is a skill published in the GitHub repository AI-Safeter/antigravity-cli-plugin (10 stars, last pushed 5mo ago), licensed MIT. It adds 57 tokens to every session and 1,573 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to code-reviewer, differing in 1 line, and is treated as a copy.
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