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hzhyjr2021-beep

smart-site-selection-skill

by qiuhe · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install smart-site-selection-skill
Description
专为实体商业选址设计,自动采集核心客群与经营策略,提取Top3优质地段坐标并生成宏观微观商业洞察报告。
Usage Guidance
What to check before installing: - The bundle requires an AMap Web Service API key (AMAP_WEBSERVICE_KEY). Confirm you are willing to provide that key and that you trust the unknown source; the top-level registry metadata incorrectly omitted this requirement. - The package mixes Python code with an npm-style package.json (versions differ: package.json v2.1.0 vs skill v1.0.0). This is a packaging inconsistency — ask the author or inspect the repository origin before trusting it. - The code calls only AMap endpoints and writes files to /tmp and the current directory; it does not phone home to unexpected domains. Still, review scripts/site_selection_engine.py and report_builder.py locally to confirm no hidden endpoints are added. - If you will supply a real AMAP key, run the skill in a sandbox or with a scoped/test key first, and inspect generated output and logs. - If you need stronger assurance: request the skill author/maintainer, a homepage, or a checksumed release (GitHub release) and confirm the exact expected env vars in the registry metadata. The current metadata mismatch is the main reason to treat this as suspicious rather than benign.
Capability Analysis
Type: OpenClaw Skill Name: smart-site-selection-skill Version: 1.0.0 The skill bundle is a legitimate business intelligence tool for site selection using the AutoNavi (AMap) LBS API. It implements a structured SOP in SKILL.md that enforces user input validation (Physical Blockage) and delegates data processing to a Python backend to prevent AI hallucinations. The code in main.py and scripts/site_selection_engine.py handles API requests with appropriate rate-limiting (time.sleep) and generates local HTML reports using ECharts. No evidence of data exfiltration, malicious command execution, or harmful prompt injection was found.
Capability Assessment
Purpose & Capability
The skill's core purpose (select top-3 coordinates via AMap and hand off deep checks to a Python engine) is coherent with the code: main.py enforces AMAP key presence and the scripts call AMap APIs. However registry-level metadata provided above claims no required env vars while SKILL.md, package.json.openclaw.requires, and main.py all expect AMAP_WEBSERVICE_KEY. This mismatch (declared NONE vs actual requirement) is an incoherence that could cause misconfiguration or unexpected prompts for credentials.
Instruction Scope
SKILL.md defines a tight SOP: request core business params, ONLY fetch Top-3 coordinates in the agent layer, and delegate traffic/competitor queries to the Python engine. The code follows that flow (main.py enforces parameter collection and scripts/site_selection_engine.py performs deeper AMap queries). The SKILL.md lists dependent skills (searxng, proactive-agent) that are not invoked in the provided Python code — this is a mild scope mismatch but not clearly malicious.
Install Mechanism
No install spec (instruction-only at registry level) and packaged files are local — there is no external download URL or extraction step. That lowers install risk. Oddity: package.json exists and lists dependencies like 'matplotlib' and 'requests' in an npm-style file (and 'engines' lists python/node). This mix of Node-style manifest with Python runtime is inconsistent and should be reviewed, but it is not an immediate code-execution red flag by itself.
Credentials
The runtime needs a single external credential (AMAP_WEBSERVICE_KEY) which is proportionate to a mapping/LBS skill. The problem is the top registry block incorrectly said 'Required env vars: none' while SKILL.md, package.json and main.py require AMAP_WEBSERVICE_KEY and the code uses it directly for requests to restapi.amap.com. That metadata mismatch could mislead users into providing keys unexpectedly. No other unrelated secrets are requested.
Persistence & Privilege
The skill does not request permanent 'always' presence and uses normal file outputs only: it writes a temporary state file to /tmp/site_selection_state.json and writes HTML reports to the current working directory. It does not modify other skills or system-wide agent settings in the provided code.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install smart-site-selection-skill
  3. After installation, invoke the skill by name or use /smart-site-selection-skill
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
smart-site-selection-skill 1.0.0 – 首个公开版本 - 支持通过关键词自动触发实体商业选址分析流程。 - 内置参数强校验,追问客户核心客群与经营战略,缺失即强制阻断。 - 自动调用高德地图,仅获取 Top 3 地段名称与经纬度坐标。 - 生成市场前景定调与三大地段优劣点评文本,避免任何自造数据。 - 清晰分工:AI 负责逻辑与文本生成,Python 后端负责数据抓取、评分与报告排版。 - 报告输出为 HTML 文件,含交互式可视化与多维评估矩阵。
Metadata
Slug smart-site-selection-skill
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is smart-site-selection-skill?

专为实体商业选址设计,自动采集核心客群与经营策略,提取Top3优质地段坐标并生成宏观微观商业洞察报告。 It is an AI Agent Skill for Claude Code / OpenClaw, with 130 downloads so far.

How do I install smart-site-selection-skill?

Run "/install smart-site-selection-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is smart-site-selection-skill free?

Yes, smart-site-selection-skill is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does smart-site-selection-skill support?

smart-site-selection-skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created smart-site-selection-skill?

It is built and maintained by qiuhe (@hzhyjr2021-beep); the current version is v1.0.0.

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