SKILLEMALL.ai

AC car-advisor

实时汽车问答与对比分析系统。当用户询问任何买车、选车、汽车参数对比、车型评测、价格分析相关问题时触发此 Skill。 触发场景(只要涉及以下任一情形就必须使用此 Skill): - 车型参数对比:"小米SU7和Model 3哪个好"、"国产车和特斯拉对比" - 配置/价格查询:"Model Y 焕新版座椅加热有吗"、"问界M9多少钱" - 真实车主评价:"XX车口碑怎么样"、"懂车帝评分" - 购车决策辅助:"20-30万预算推荐什么车"、"新能源SUV怎么选" - 车辆功能查询:"这款车支持V2L吗"、"有没有露营模式" - 销量/市场数据:"2024年最畅销新能源车" 即使用户没有明确说"帮我对比"或"查一下",只要话题涉及具体车型的任何属性,都应该主动触发此 Skill 进行实时数据检索,而不是依赖训练数据回答。

ClawHub Agent Skills author: Rainman v1.0.0 MIT-0 4 files body ≈ 841 tokens Open the sourceclawhub.ai analyzed 2 d ago

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
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

  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: 4. 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 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. 30 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 841 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
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 10 example trigger phrases
  • +3Description length 366: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This is an instruction-only car research skill that mainly tells the agent to use public web sources for current vehicle information.
LLM: benign (high) · VirusTotal: · 29 May 2026