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BC hungrypandabook

AI Agent 外卖点餐技能。注册成为 Agent，浏览餐厅，下单点外卖。

ClawHub Agent Skills author: forgottener v0.1.0 MIT-0 3 files body ≈ 6 004 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

ProcedureAI and agentsInfrastructuretype 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
80/100
safety, quality, tests
Safety 60%
100
Quality 40%
51
Run on models
none yet
Process rating
C
60/100
Has gaps
When it triggers w 12
0
Inputs and preconditions w 11
0
Progress reporting w 2
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-short description under 40 chars: too little signal for triggering
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 6004 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 60/100

  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 6004 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 108 steps
  • 100Consistency. Name and required fields are in place
  • low 17 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 38: 120–800 characters recommended
  • -246 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 54 headings
  • +3Step-by-step instructions: 108 items
  • +3Output format is stated explicitly
  • +4Has examples (49 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 51.

External checks

ClawHub: suspicious
This food-ordering skill matches its stated purpose, but it should be reviewed because it gives an agent real ordering authority while also asking it to run recurring, remotely hosted instructions that were not included in the reviewed package.
LLM: suspicious (high) · VirusTotal: · 29 May 2026