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BC store-site-analysis

基于高德开放平台的商铺选址分析 Skill。支持单地址选址分析（竞品搜索、配套评估、交通态势、热力图可视化）和多地址对比分析（雷达图、柱状图、评分排名、聚合地图）。让 AI Agent 一句话完成开店选址评估。

ClawHub Agent Skills author: wukongmazi v1.0.3 MIT-0 8 files body ≈ 895 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

基于高德开放平台的商铺选址分析 Skill。支持单地址选址分析（竞品搜索、配套评估、交通态势、热力图可视化）和多地址对比分析（雷达图、柱状图、评分排名、聚合地图）。让 AI Agent 一句话完成开店选址评估。

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

AnalyzerAI and agentstype 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
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
72
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-high-entropy-token heatmap_template.html:75
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    icon:new AMap.Icon({size:new AMap.Size(24,24),image:"data:image/png;base64,iVBO…XEx+BUmj…Dod/BRozHGCARNlMTEQ
    detector
  • low Secrets in code secret-high-entropy-token heatmap_template.html:88
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    icon:new AMap.Icon({size:new AMap.Size(24,24),image:"data:image/png;base64,iVBO…iiw+gk6C…6UF/QV8U…3zD
    detector

Files scanned: 8. 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 62/100

  • 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
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. No external tools needed
  • 100Steps. 28 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 895 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)
  • +3Description length 105: 120–800 characters recommended
  • +1No license
  • +2Single-language instructions
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 28 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)

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

External checks

ClawHub: clean
This skill does what it advertises: it sends address/location queries to AMap and writes local HTML map reports for store site analysis.
LLM: benign (high) · VirusTotal: · 21 Jun 2026