SKILLEMALL.ai

AD ctrip-compare

携程跟团游产品快速对比分析。触发条件: (1) 用户提供携程旅游产品URL(vacations.ctrip.com/travel/detail/ 或 vacations.ctrip.com/tour/detail/) (2) 用户提供携程搜索列表页URL(vacations.ctrip.com/list/ 开头) 支持场景: (1) 用户提供多个携程跟团游URL,要求对比分析 (2) 用户提供搜索列表页URL,自动提取产品后对比分析 (3) 用户说"帮我对比这几个携程产品"、"分析一下这几个旅行产品" (4) 用户要求从携程产品中选出最优方案 工作流程: - 产品URL模式:确认日期 → 一键提取数据 → 并行压缩摘要 → 询问偏好 → 分析对比 → 生成Markdown - 搜索页模式:搜索页提取产品URL → 确认日期 → 一键提取数据 → 并行压缩摘要 → 询问偏好 → 分析对比 → 生成Markdown

ClawHub Agent Skills author: zhangxiaoshuai v0.1.1 MIT-0 5 files body ≈ 2 047 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
D
46/100
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

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 · 0

✓ No critical or high findings

Files scanned: 5. 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 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 42 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2047 tokens
  • 100Running it twice. No mutating operations
  • low 11 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 413: enough signal without eating the budget
  • +4Structure: 30 headings
  • +3Step-by-step instructions: 42 items
  • +4Has examples (16 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
This travel-comparison skill mostly does what it claims, but it asks for broad control over the user's local browser that deserves review before installation.
LLM: suspicious (high) · VirusTotal: · 29 May 2026