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BD skill-composer

L2 编排层 - 智能技能编排引擎。自动编排多技能协作流程，分析技能依赖关系，优化执行策略（并行/串行决策）。

ClawHub Agent Skills author: pagoda v0.1.0 MIT-0 7 files body ≈ 1 040 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorInfrastructuretype 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
83/100
safety, quality, tests
Safety 60%
95
Quality 40%
65
Run on models
none yet
Process rating
D
49/100
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token package-lock.json:275
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "integrity": "sha5…ywo+qwL+oL8H…C1U+vRfLQDvw==",
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:291
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-Yqfm+XDx0+Prh3…1yC+JWZ2…IL7+vK+Clp7…D7g==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:304
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…xZl+RoGR…fbT/ZgrF…0EA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:317
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…3bJ+V0If…IXN+CL65…a4w==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:333
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "integrity": "sha5…H47+FFon…OsV/4+RRsz…0ig==",
    quoted

Files scanned: 6. 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")
  • note frontmatter-key unknown frontmatter key "origin"
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 49/100

  • 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 (skill-composer) differs from the folder (skill-composer-pro)
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 23 steps
  • 100Execution cost. Instruction body is 1040 tokens
  • 100Running it twice. No mutating operations
  • low 14 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 55: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -218 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 32 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (16 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: suspicious
This looks like a legitimate workflow-planning skill, but it asks for broad write and command-execution authority while describing automatic retries and fallback behavior without clear user approval boundaries.
LLM: suspicious (high) · VirusTotal: · 29 May 2026