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AF py_mnn_kb

Local vector knowledge base with GraphRAG retrieval (vector + BM25 + knowledge graph). Use this skill when the user mentions: "查知识库", "加入知识库", "记住这个", "save to KB", "add to knowledge base", "query knowledge base", "记录一下", or similar intent to store or retrieve private knowledge.

ClawHub Agent Skills author: er6y v1.0.0 MIT-0 10 files body ≈ 1 354 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 37/100 · Will not run — References files that are not bundled: assets/knowledge_bases

ReferenceInfrastructuretype 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
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
F
37/100
Will not run
References files that are not bundled: assets/knowledge_bases
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: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning missing-ref reference to a missing file: assets/knowledge_bases
  • note frontmatter-key unknown frontmatter key "disable"

Process rating: all ten parameters 37/100

Will not run. References files that are not bundled: assets/knowledge_bases
  • 0Tools and files. 1 referenced file(s) missing: assets/knowledge_bases
  • 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
  • 40Consistency. Frontmatter name (py_mnn_kb) differs from the folder (py-mnn-kb)
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 8 steps
  • 100Execution cost. Instruction body is 1354 tokens
  • 100Running it twice. Mutating operations check current state

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
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 279: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 8 items
  • +4Has examples (13 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
This private knowledge-base skill appears useful, but it can persist sensitive user content and may send retrieved KB context to external LLM APIs without sufficiently clear user control.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026