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导购结构分析
作者
Xtechmerge.AI
· GitHub ↗
· v1.0.0
· MIT-0
92
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当前安装
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版本数
在 OpenClaw 中安装
/install retail-clerk-structure-analysis
功能描述
导购结构分析工具。分析门店导购的表现结构，识别导购波动对门店业绩波动的贡献度。 核心能力： 1. 导购表现结构分析（人效分布、帕累托分析） 2. TOP/腰部/尾部导购识别 3. 业绩集中度评估 4. 导购波动归因（各导购对门店业绩变化的贡献度） 5. 增长型vs下滑型导购分类 6. 基于累计贡献度的关键人识别...
安全使用建议
This skill's purpose (analyzing store clerk performance) is reasonable, but the implementation has a hidden dependency: analyze.py inserts a hard-coded absolute path and imports get_copilot_data from an external/local module (api_client) that is not bundled or documented. That module may call internal APIs or read credentials/config files on your system. Before installing or running this skill: 1) Ask the author to provide or document api_client and get_copilot_data (show the code and where it contacts). 2) Require the skill to be self-contained or to declare any environment variables, hosts, or credentials it needs. 3) If you must run it, inspect the api_client code for network calls and credential access, and run the skill in an isolated environment (sandbox/container) with no sensitive credentials mounted. 4) Prefer a version that packages its dependencies (or uses standard pip/requirements) rather than referencing a user-specific path. If the author cannot explain or remove the hard-coded path and disclose the external endpoints/credential usage, treat the skill as untrusted.
功能分析
Type: OpenClaw Skill
Name: retail-clerk-structure-analysis
Version: 1.0.0
The skill bundle is a legitimate tool for retail performance analysis, focusing on clerk productivity, Pareto distributions, and sales attribution. The code in `analyze.py` performs standard statistical calculations (such as variation coefficients and contribution percentages) and fetches data through an internal API client. While it contains hardcoded local file paths for environment setup, these appear to be development artifacts rather than malicious indicators or security vulnerabilities, and the instructions in `SKILL.md` are strictly functional.
能力评估
Purpose & Capability
The skill claims to analyze clerk performance and requires no external credentials or binaries, but analyze.py inserts a hard-coded path '/Users/yangguangwei/.openclaw/workspace-front-door' and imports get_copilot_data from api_client. That local dependency is not declared in SKILL.md or manifest and suggests the skill expects access to a private project or internal API rather than being self-contained.
Instruction Scope
SKILL.md presents a clean API (analyze(...)) and no mention of reading local modules or contacting internal services, yet the runtime code calls fetch_clerk_data which delegates to get_copilot_data(endpoint). The instructions do not document what get_copilot_data does, what endpoints/hosts it calls, or what credentials/config it requires — granting the skill broad, undocumented discretion to access local modules and remote data.
Install Mechanism
There is no install spec (instruction-only) which is low risk in general. However, the shipped analyze.py expects a non-packaged local dependency via modification of sys.path. That is an unusual packaging choice: instead of bundling or documenting the dependency, the code reaches into a specific user's home directory. This could fail or cause unexpected imports if that path exists on the host.
Credentials
The manifest declares no required environment variables or credentials, but the code relies on api_client.get_copilot_data — a function likely to access remote APIs and possibly use credentials or local config files. Because those credentials/configs are not declared, the skill may end up accessing secrets or internal endpoints without the user being warned.
Persistence & Privilege
The skill does not request always:true, does not modify other skills' configs, and has no install script. It only adjusts sys.path at runtime to import a module; it does not persistently install or enable itself.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install retail-clerk-structure-analysis - 安装完成后，直接呼叫该 Skill 的名称或使用
/retail-clerk-structure-analysis触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release: 支持导购表现结构、波动归因、关键人识别
元数据
常见问题
导购结构分析 是什么？
导购结构分析工具。分析门店导购的表现结构，识别导购波动对门店业绩波动的贡献度。 核心能力： 1. 导购表现结构分析（人效分布、帕累托分析） 2. TOP/腰部/尾部导购识别 3. 业绩集中度评估 4. 导购波动归因（各导购对门店业绩变化的贡献度） 5. 增长型vs下滑型导购分类 6. 基于累计贡献度的关键人识别... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 92 次。
如何安装 导购结构分析？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install retail-clerk-structure-analysis」即可一键安装，无需额外配置。
导购结构分析 是免费的吗？
是的，导购结构分析 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
导购结构分析 支持哪些平台？
导购结构分析 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 导购结构分析？
由 Xtechmerge.AI（@gwyang7）开发并维护，当前版本 v1.0.0。
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