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BF 蜂兵虾将

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ClawHub Agent Skills author: e2e5g v1.4.1 34 files · 1 script body ≈ 1 520 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 27/100 · Will not run — References files that are not bundled: scripts/memory-v2.ts

ProcedureInfrastructuretype 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
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
Run on models
none yet
Process rating
F
27/100
Will not run
References files that are not bundled: scripts/memory-v2.ts
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

The same skill appears in 2 more places: ClawHub, ClawHub

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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: 34. 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 description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: scripts/memory-v2.ts

Process rating: all ten parameters 27/100

Will not run. References files that are not bundled: scripts/memory-v2.ts
  • 0Tools and files. 1 referenced file(s) missing: scripts/memory-v2.ts
  • 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 (蜂兵虾将) differs from the folder (bing-bing-xia-jiang)
  • 75Steps. 3 steps
  • 100Execution cost. Instruction body is 1520 tokens
  • 100Running it twice. No mutating operations

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 222: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 3 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (2 of 5)

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

External checks

ClawHub: suspicious
This skill is not clearly malicious, but it stores and reuses user history, workflow data, and personal profile inferences more broadly than its safeguards explain.
LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026