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CD adversarial-review

开发完成后的三方对抗式代码评审闭环：蓝军（敌意审查，须给证据链）→ 第三方（独立审计，不信双方文档、只读代码，专找"修改引入的新缺陷"并稽核蓝军漏审的维度）→ 中立裁定（逐条采纳/驳回、审查双方共同前提）。当用户说"蓝军评审""第三方复核""对抗性审查""红蓝互搏""三方评审""交叉验证""发布前审查""帮我挑刺""adversarial review""red team review""pre-release review""critique this""find bugs in my code"或要求提升代码质量、准备发布前把关时使用。也适用于用户想把当前会话变成"多个 Agent 互搏"来提升代码水平的场景。

ClawHub Agent Skills author: LA v2.5.1 MIT-0 12 files · 4 scripts body ≈ 1 508 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

开发完成后的三方对抗式代码评审闭环：蓝军（敌意审查，须给证据链）→ 第三方（独立审计，不信双方文档、只读代码，专找"修改引入的新缺陷"并稽核蓝军漏审的维度）→…

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

AnalyzerAI and agentsSoftware 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
C
89/100
safety, quality, tests
Safety 60%
97
Quality 40%
77
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

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 examples/sample-review.md:56
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (test fixture / example file; quoted — discussed, not commanded)
    - **触发条件**：英文用户说 `code review`、`red team review`、`find bugs in my code`。
    fixturequoted
  • low Risky intent intent-offensive-security examples/sample-review.md:58
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (test fixture / example file; quoted — discussed, not commanded)
    - **修复方向**：补 `red team review` / `pre-release review` / `critique this` / `find bugs in my code`。
    fixturequoted
  • low Risky intent intent-offensive-security SKILL.md:3
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
    description: 开发完成后的三方对抗式代码评审闭环：蓝军（敌意审查，须给证据链）→ 第三方（独立审计，不信双方文档、只读代码，专找"修改引入的新缺陷"并稽核蓝军漏审的维度）→ 中立裁定（逐条采纳/驳回、审查双方共同前提）。当用户说"蓝军评审""第三方复核""对抗性审查""红蓝互搏""三方评审""交叉验证""发布前审查""帮我挑刺""adversarial review""red team
    quoted

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. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (adversarial-review) differs from the folder (three-party-adversarial-review)
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 100Steps. 47 steps
  • 100Execution cost. Instruction body is 1508 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
  • -238 emoji in the instructions: noise for the model
  • -33 of 4 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +5Description quotes 7 example trigger phrases
  • +3Description length 311: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 47 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: suspicious
The skill is a coherent adversarial code-review workflow, but it can be triggered broadly and then spawn agents, run commands, write reports, and edit code without a clear confirmation checkpoint.
LLM: suspicious (high) · VirusTotal: · 27 Sept 2026