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BD code-reviewer

本技能从 6 个维度对代码进行全面审核：安全性、性能、代码质量、错误处理、测试和文档。适用于审核代码变更、Pull Request 或整个代码库（支持所有主流编程语言）。触发词包括：「帮我 review 这段代码」「检查安全问题」「审查这个 PR」「找出代码中的 Bug」，或用户请求代码质量分析时使用。技能内置自动化分析脚本、安全规则库、各语言最佳实践文档，并可生成可视化 HTML 审核报告。

ClawHub Agent Skills author: nameused v1.0.1 MIT-0 9 files body ≈ 1 413 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

本技能从 6 个维度对代码进行全面审核：安全性、性能、代码质量、错误处理、测试和文档。适用于审核代码变更、Pull Request 或整个代码库（支持所有主流编程语言）。触发词包括：「帮我 review 这段代码」「检查安全问题」「审查这个 PR」「找出代码中的…

As a process D 46/100 · 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
B
88/100
safety, quality, tests
Safety 60%
97
Quality 40%
74
Run on models
none yet
Process rating
D
46/100
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

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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Risky intent intent-offensive-security references/security-rules.md:10
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | Privilege escalation | Role check missing before sensitive operation | All |
  • low Risky intent intent-offensive-security references/security-rules.md:197
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | **High** | Sensitive data exposure, privilege escalation, SSRF, deserialization flaws | `pickle.loads(request_data)`, missing auth on admin endpoints |
  • low Risky intent intent-offensive-security references/severity-guide.md:43
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    **Definition:** Issues that could lead to data breaches, privilege escalation, or significant security weaknesses under certain conditions. Should be fixed before merge.

Files scanned: 9. 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 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 62 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1413 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 198: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 62 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This is a coherent local code review helper that reads user-selected code, runs local analysis scripts, and optionally writes a local HTML report.
LLM: benign (high) · VirusTotal: · 20 Jun 2026