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省柴柴·出行规划与订票助手:你的旅行生活方式好帮手。基于目的地、天数、兴趣和预算,智能规划行程路线、城市顺序和住宿区域;支持机票/高铁查询、酒店与景点推荐、美食发现;生成 HTML 行程单,让每次出行都省心又划算。用户说"机票""酒店""门票""出行""订票""规划行程""行程""旅行""比价""亲子""自由行""自驾"或类似旅行意图时调用。

ClawHub Agent Skills author: marywbrown v1.0.6 MIT-0 11 files body ≈ 611 tokens Open the sourceclawhub.ai analyzed 2 d ago

省柴柴·出行规划与订票助手:你的旅行生活方式好帮手。基于目的地、天数、兴趣和预算,智能规划行程路线、城市顺序和住宿区域;支持机票/高铁查询、酒店与景点推荐、美食发现;生成 HTML…

As a process F 35/100 · Will not run — References files that are not bundled: references/output-rules.md, references/qa-handbook.md

ProcedureCommercetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
98
Quality 40%
61
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/output-rules.md, references/qa-handbook.md
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. 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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Obfuscation obf-base64-blob scripts/gen-itinerary-html.js:215
    Long base64-looking blob (detector / deny-list definition)
    const LOGO…B64 = '/9j/4AAQ…AAD/2wBD…Gxr/2wBD…oaG
    detector
  • low Secrets in code secret-high-entropy-token scripts/gen-itinerary-html.js:215
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const LOGO…B64 = '/9j/4AAQ…AAD/2wBD…Gxr/2wBD…oaG
    quoted

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/output-rules.md
  • warning missing-ref reference to a missing file: references/qa-handbook.md
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "description_en"
  • note frontmatter-key unknown frontmatter key "visibility"
  • note frontmatter-key unknown frontmatter key "agent_created"
  • note frontmatter-key unknown frontmatter key "icon"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/output-rules.md, references/qa-handbook.md
  • 0Tools and files. 2 referenced file(s) missing: references/output-rules.md, references/qa-handbook.md
  • 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
  • 100Steps. 37 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 611 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
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 172: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 37 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (1 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

External checks

ClawHub: suspicious
The travel-booking skill is mostly purpose-aligned, but it hides recommendation/link sources and sends detailed trip data to a hardcoded cloud service, so users should review it before installing.
LLM: suspicious (high) · 7 Aug 2026