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AF skill-chain

Supply chain intelligence for OpenClaw skills. Use when analyzing the local skill ecosystem, understanding tool and package dependencies, discovering skill categories, mapping relationships between skills, checking security posture, auditing skill health, detecting overlaps, or generating an ecosystem health report. Trigger on "analyze my skills", "skill supply chain", "what tools do my skills use", "skill dependencies", "skill inventory", "ecosystem report", "which skills use X package", "skill categories", "popular skills", "skill security", "skill health", "skill completeness", "overlapping skills".

ClawHub Agent Skills author: hyx-cn v1.0.1 MIT-0 7 files body ≈ 1 440 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 39/100 · Will not run — References files that are not bundled: scripts/*.py, scripts/ontology.py

AnalyzerData and analyticsInfrastructuretype 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
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
F
39/100
Will not run
References files that are not bundled: scripts/*.py, scripts/ontology.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/*.py
  • warning missing-ref reference to a missing file: scripts/ontology.py

Process rating: all ten parameters 39/100

Will not run. References files that are not bundled: scripts/*.py, scripts/ontology.py
  • 0Tools and files. 2 referenced file(s) missing: scripts/*.py, scripts/ontology.py
  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 7 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1440 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
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 13 example trigger phrases
  • +3Description length 609: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 7 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

External checks

ClawHub: clean
SkillChain is a disclosed, user-run tool for inventorying local OpenClaw skills, with privacy considerations around saved local metadata and optional online enrichment.
LLM: benign (high) · VirusTotal: · 29 May 2026