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DC agent-selector

(no description)

Not recommendedlow grade D
ClawHub Agent Skills author: Krislu v1.0.3 MIT-0 80 files body ≈ 1 535 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype 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
D
56/100
safety, quality, tests
Safety 60%
94
Quality 40%
0
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
When it triggers w 12
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Add a description to the frontmatter: without it the skill never triggers.
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 · 6

✓ No critical or high findings

Medium and low: 6
  • low Risky intent intent-offensive-security agency-agents/engineering/engineering-threat-detection-engineer.md:33
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - 通过 atomic red team 测试或紫队演练验证检测是否真的能触发
  • low Secrets in code secret-high-entropy-token agency-agents/engineering/engineering-threat-detection-engineer.md:244
    High-entropy token-like string (may be an id, hash or a credential)
    run: pip install sigma-cli pySigma-backend-splunk pySi…der
  • low Secrets in code secret-high-entropy-token agency-agents/engineering/engineering-threat-detection-engineer.md:283
    High-entropy token-like string (may be an id, hash or a credential)
    pySi…der \
  • low Risky intent intent-offensive-security agency-agents/engineering/engineering-threat-detection-engineer.md:404
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    4. 使用 atomic red team 测试 T1003.001 进行验证
  • low Risky intent intent-offensive-security agency-agents/engineering/engineering-threat-detection-engineer.md:471
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - 运行 atomic red team 测试或手动模拟确认检测对目标技术触发
  • low Secrets in code secret-high-entropy-token agency-agents/game-development/unreal-engine/unreal-multiplayer-architect.md:299
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - 为开放世界游戏实现 `URep…n2D`：仅将空间格子内的 Actor 复制给附近客户端
    quoted

Files scanned: 80. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 48 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1535 tokens
  • 100Running it twice. No mutating operations
  • low 13 top-level sections: this looks like several domains in one skill

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)
  • +3Description length 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -239 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 40 headings
  • +3Step-by-step instructions: 48 items
  • +4Has examples (18 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: suspicious
The selector code is mostly read-only, but the bundled prompt library includes under-scoped guidance for sensitive actions like payments, production deployments, user-data experiments, public-content manipulation, and shared memory.
LLM: suspicious (high) · VirusTotal: · 29 May 2026