SKILLEMALL.ai
GitHub ↗ RU Sign in

AD code-review

AI 驱动的代码审查工具。对代码变更进行多维度审查，输出结构化的 Review 意见。 **当以下情况时使用此 Skill**: (1) 需要对代码进行 Code Review (2) 需要审查 PR/MR 的代码变更 (3) 用户提到"code review"、"代码审查"、"帮我看看代码"、"这段代码有问题吗" (4) 需要检查代码安全性、性能、可维护性 (5) 提交代码前的自查 (6) 用户提到"PR review"、"代码质量"、"技术债务"

ClawHub Agent Skills author: VelenGao v1.0.0 MIT-0 5 files body ≈ 964 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerSoftware 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
D
41/100
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
This is a copy of a skill from another catalog; the rating counts the canonical one: code-review (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: 5. 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 41/100

  • 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
  • 40Consistency. Frontmatter name (code-review) differs from the folder (ai-code-audit)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 32 steps
  • 100Execution cost. Instruction body is 964 tokens
  • 100Running it twice. No mutating operations

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
  • -241 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 228: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (11 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This is a coherent code-review skill that may read local git diffs when asked to review recent changes, with no evidence of hidden exfiltration, persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 28 May 2026