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AF food-travel

Plan food-driven travel experiences — recommend best cities for a dish or cuisine, generate city food maps with meal-by-meal restaurant routes, and build complete food-centric itineraries with flights, hotels, and dining schedules. Use when the user asks about food travel, food trips, eating tours, food guides, must-eat dishes, restaurant recommendations for travel, or phrases like "我想吃烤鸭去哪", "成都美食攻略", "3天吃遍西安", "周末广州美食游", "为了吃去旅行", "plan a food trip".

ClawHub Agent Skills author: ZzziLin v1.0.0 MIT-0 2 files body ≈ 1 107 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 56/100 · Will not run — References files that are not bundled: {url}, {picUrl}, {mainPic}

GeneratorInfrastructuretype 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
F
56/100
Will not run
References files that are not bundled: {url}, {picUrl}, {mainPic}
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: {url}
  • warning missing-ref reference to a missing file: {picUrl}
  • warning missing-ref reference to a missing file: {mainPic}

Process rating: all ten parameters 56/100

Will not run. References files that are not bundled: {url}, {picUrl}, {mainPic}
  • 0Tools and files. 3 referenced file(s) missing: {url}, {picUrl}, {mainPic}
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 60Result and completion. Output format stated, no completion criterion
  • 60Failures and branches. 2 branches
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 19 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1107 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)
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 6 example trigger phrases
  • +3Description length 456: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 19 items
  • +3Output format is stated explicitly
  • +4Has examples (9 code blocks)

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

External checks

ClawHub: clean
This is a food-travel planning skill that uses external search and travel lookup results in a disclosed, purpose-aligned way, with normal caution around third-party links.
LLM: benign (high) · VirusTotal: · 29 May 2026