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AC food-safety-butler

餐饮食安合规管家（单店 / Pro 审计 / 集团风控 三层）。This skill should be used when restaurant operators mention "食安检查""迎检""办证""后厨布局""市场监管""4D管理""健康证""食品经营许可证""客诉异物""职业打假""集团食安审计""合规体系升级""客诉溯源""飞行检查""供应商准入""舆情风险""HACCP""GB 31654""ISO22000". It turns 《食品安全法》/ GB 31654-2021 into executable red-yellow-green checklists, license workflows, crisis-PR scripts, HACCP gap reports, and group risk directives for F&B practitioners.

ClawHub Agent Skills author: MonsterDT v1.0.0 MIT-0 15 files body ≈ 1 568 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

餐饮食安合规管家（单店 / Pro 审计 / 集团风控 三层）。This skill should be used when restaurant operators mention…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureProcurementData and analyticsSecuritytype 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%
80
Run on models
none yet
Process rating
C
53/100
Has gaps
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

    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: 15. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "pricing"

    Process rating: all ten parameters 53/100

    • 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
    • 100Tools and files. No external tools needed
    • 100Steps. 28 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1568 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -413 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +3Description length 402: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 28 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: suspicious
    This food-safety advisory skill is mostly coherent, but it needs review because one crisis-response instruction encourages downplaying serious incidents and the skill asks for sensitive business data without clear privacy guidance.
    LLM: suspicious (high) · VirusTotal: · 20 Jul 2026