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 Xiaowen-Jiang/agent-enterprise --skill code_reviewgit clone --depth 1 https://github.com/Xiaowen-Jiang/agent-enterpriseWrote 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/xiaowen-jiang/agent-enterprise/code_review)<a href="https://agentmods.dev/skills/xiaowen-jiang/agent-enterprise/code_review"><img src="https://agentmods.dev/badge/skills/xiaowen-jiang/agent-enterprise/code_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/xiaowen-jiang/agent-enterprise/code_review"><img src="https://agentmods.dev/badge/skills/xiaowen-jiang/agent-enterprise/code_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 | $0.00015 | $0.00292 |
| Opus 5.5 | $0.00006 | $0.00117 |
| Sonnet 5.5 | $0.00003 | $0.00058 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
Code 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 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
Process
- Read the target file(s) using the filesystem tools
- Security check: Look for SQL injection, XSS, command injection, hardcoded secrets, unsafe deserialization
- Code quality: Check naming conventions, function length, duplication, complexity
- Error handling: Verify edge cases, null checks, proper exception handling
- Style & readability: Consistent formatting, meaningful comments, clear variable names
- Performance: Identify obvious inefficiencies, unnecessary loops, memory issues
Output Format
Provide structured feedback using severity levels:
- CRITICAL: Security vulnerabilities or bugs that will cause failures
- WARNING: Code smells, potential issues, or maintainability concerns
- SUGGESTION: Style improvements, better patterns, or minor optimizations
- GOOD: Highlight well-written parts (positive feedback matters)
Guidelines
- Be specific — reference line numbers and exact code
- Explain WHY something is an issue, not just WHAT
- Suggest concrete fixes with code examples
- Start with a brief summary before detailed findings
- End with an overall assessment (approve / request changes)
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 · 34 lines · 15 tokens per session scan A 8ec96ac69922
Code Review is a skill published in the GitHub repository Xiaowen-Jiang/agent-enterprise (52 stars, last pushed 6mo ago), licensed MIT. It adds 15 tokens to every session and 292 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 2026-08-30.
Other skills, from other repositories
code-review
Reviews Spec Kit code changes for consistency with applicable design documents, positive and negative test coverage, regression evidence for bug fixes, and consistent repository terminology. Use when reviewing a diff or pull request. Do not use for implementing changes or posting GitHub review actions.
ai-agent-evaluation-benchmarking
Autonomous AI agent benchmark evaluation register: task completion rates, planning accuracy, tool invocation precision, and cost benchmarks.
ce-code-review
Review a named diff or PR for bugs, regressions, tests, and standards. Use when asked to review code or when a shipping skill needs a review receipt. Use when asked to apply this review's findings locally. Use ce-resolve-pr-feedback for feedback already left on a PR.
ce-resolve-pr-feedback
Judge PR feedback centrally, apply valid fixes, and complete review conversations with publication verified. Use when addressing feedback already left on a PR, preparing local fixes for a caller to publish, or completing a saved feedback batch. Use ce-code-review for reviewing code before feedback exists.
code-review
Review code for quality, maintainability, and correctness.
sage-review
Deep, platform-neutral code review for PRs and CRs in ONE thorough single pass — design reasoning (Problem Worth Solving & Solution Fit) as one dimension alongside the 9 code-level dimensions, with chain-of-consequences, self-critique, and draft-only comments. The single app-owned source of truth.