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BD travel-evening-micro-vacation

像一个经常出差的朋友，根据城市/酒店/地标与时段，用共情开场 + 嵌入式选项智能捕捉隐性需求（散步/喝一杯/放松等），不用固定菜单；用系统时间编排松弛的时间线，白天追问能玩多久、晚间追问是否早起；联网整理可执行方案；输出氛围图、故事感时间线、情境文案、高德导航链接、小红书关键词，结尾推你出门。全程提供强情绪价值，温暖但克制。当用户只报位置、想玩一下、出差间隙、会后放空、赶交通、酒店周边或要导航链接时使用。

ClawHub Agent Skills author: Keyi v1.0.0 MIT-0 11 files body ≈ 2 133 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

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
83/100
safety, quality, tests
Safety 60%
88
Quality 40%
76
Run on models
none yet
Process rating
D
43/100
Unfinished process
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 4

✓ No critical or high findings

Medium and low: 4
  • medium Exfiltration net-credential-use references/amap-poi-search.md:33
    Credential used in a network call (verify the destination is the intended service)
    curl -s "https://restapi.amap.com/v3/place/text?key=…&keywords=北秀观云&city=杭州&citylimit=true&extensions=all&offset=5"
  • medium Exfiltration net-credential-use references/amap-poi-search.md:51
    Credential used in a network call (verify the destination is the intended service)
    curl -s "https://restapi.amap.com/v3/place/text?key=…&keywords=…&city=杭州&citylimit=true&offset=3"
  • low Exfiltration exfil-secret-in-url references/amap-poi-search.md:33
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
    curl -s "https://restapi.amap.com/v3/place/text?key=…&keywords=北秀观云&city=杭州&citylimit=true&extensions=all&offset=5"
    placeholder
  • low Exfiltration exfil-secret-in-url references/amap-poi-search.md:51
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
    curl -s "https://restapi.amap.com/v3/place/text?key=…&keywords=…&city=杭州&citylimit=true&offset=3"
    placeholder

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")

Process rating: all ten parameters 43/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (travel-evening-micro-vacation) differs from the folder (bleisure-micro-vacation)
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 55 steps
  • 100Execution cost. Instruction body is 2133 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • low 15 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 204: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 55 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (7 of 7)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
This travel-planning skill is mostly coherent, but it automatically uses powerful local browser automation and stores travel history in ways users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026