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代码 Review 助手。分析 Git diff 或代码片段，输出结构化中文 Review 报告，覆盖 Bug、安全漏洞、性能问题、可读性、最佳实践、类型安全、错误处理、测试覆盖。支持严格程度配置（信息/优化/标准/严重）和多种主流语言（Python/JS/TS/Java/Go/Rust）。支持 GitHub/GitLab PR diff 获取，支持 Markdown/JSON/HTML 多种输出格式。使用场景：用户说"帮我 review 代码"、"检查这段代码"、"review 一下最近的改动"、"review 这个 PR"、"看看这个 diff 有没有问题"、"代码审查"、"code review"、"严格模式 review"、"快速 review"。

ClawHub Agent Skills author: xonet1 v1.0.0 MIT-0 12 files body ≈ 416 tokens Open the sourceclawhub.ai↗ analyzed 21 h ago

代码 Review 助手。分析 Git diff 或代码片段，输出结构化中文 Review 报告，覆盖 Bug、安全漏洞、性能问题、可读性、最佳实践、类型安全、错误处理、测试覆盖。支持严格程度配置（信息/优化/标准/严重）和多种主流语言（Python/JS/TS/Java/Go/Rust）。支持…

As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerGitHubGitLabSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
D
39/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 39/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (code-review-assistant) differs from the folder (cody)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 25 steps
  • 100Execution cost. Instruction body is 416 tokens

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -214 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 8 example trigger phrases
  • +3Description length 332: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 25 items
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: clean
This skill is a code-review helper that reads diffs or PRs as advertised, with no evidence of hidden persistence, destructive behavior, or unrelated data exfiltration.
LLM: benign (high) · VirusTotal: · 29 May 2026