SKILLEMALL.ai

BC shop-savvy

智能购物决策助手。覆盖全网商品比价、优惠券/折扣码搜索、 产品参数对比、性价比分析、评价摘要、购买时机建议。 支持家电、数码3C、家居、母婴、美妆等品类。 帮你省钱省时间,避免冲动消费。 触发词:购物决策、比价、优惠券、买什么好、商品对比、评测、剁手前先问。

ClawHub Agent Skills author: qq435912743 v1.0.0 MIT-0 4 files body ≈ 740 tokens Open the sourceclawhub.ai analyzed 3 d ago

智能购物决策助手。覆盖全网商品比价、优惠券/折扣码搜索、 产品参数对比、性价比分析、评价摘要、购买时机建议。 支持家电、数码3C、家居、母婴、美妆等品类。 帮你省钱省时间,避免冲动消费。 触发词:购物决策、比价、优惠券、买什么好、商品对比、评测、剁手前先问。

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

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
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")
  • note frontmatter-key unknown frontmatter key "agent_created"
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "display_name_en"
  • note frontmatter-key unknown frontmatter key "description_zh"
  • note frontmatter-key unknown frontmatter key "description_en"
  • note frontmatter-key unknown frontmatter key "visibility"

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. Tools declared in frontmatter
  • 100Steps. 18 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 740 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 129: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (7 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
This shopping skill is mostly purpose-aligned, but it adds automatic persistent memory and self-modifying learning behavior that is broader than a normal shopping assistant.
LLM: suspicious (high) · 14 Aug 2026