导购结构分析

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...

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.

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.