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JW Data Analyst

作者 a85012712 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install jw-data-analyst
功能描述
数据分析助手 - 自动生成Python数据处理脚本、可视化图表、统计报告。支持Excel/CSV/JSON/数据库。觸發詞:数据分析、图表、统计、报表、可视化。
使用说明 (SKILL.md)

JW Data Analyst

数据分析智能助手,自动处理数据并生成洞察。

功能

1. 数据加载

  • Excel (.xlsx/.xls)
  • CSV/TSV
  • JSON
  • SQLite/MySQL/PostgreSQL
  • API数据源

2. 数据清洗

  • 缺失值处理(填充/删除/插值)
  • 重复值检测与去除
  • 异常值检测(IQR/Z-score)
  • 数据类型转换
  • 格式标准化

3. 统计分析

  • 描述性统计(均值/中位数/标准差)
  • 相关性分析
  • 趋势分析
  • 分组聚合
  • 时间序列分析

4. 可视化

  • 折线图(趋势)
  • 柱状图(对比)
  • 饼图(占比)
  • 散点图(相关性)
  • 热力图(矩阵)
  • 箱线图(分布)

使用方式

分析Excel文件

帮我分析这个Excel文件:[路径]

生成图表

用这个数据生成一个柱状图:[数据]

统计报告

生成数据的统计报告:[数据]

输出格式

  • 分析报告:Markdown格式
  • 图表:PNG/SVG
  • 处理后的数据:Excel/CSV
  • Python脚本:可复用的.py文件

技术栈

  • Python 3.10+
  • pandas(数据处理)
  • matplotlib/seaborn(可视化)
  • numpy(数值计算)
  • openpyxl(Excel读写)
  • sqlalchemy(数据库连接)

注意事项

  • 大文件(>100MB)需要分批处理
  • 敏感数据需脱敏后分析
  • 生成的图表默认保存到D盘
安全使用建议
This skill appears to do what it says (generate analysis scripts, charts, reports), but there are a few things to check before installing or using it. 1) Metadata mismatch: _meta.json lists a different ownerId than the registry metadata — ask the publisher to confirm authorship. 2) Do not supply production DB credentials or API keys until you confirm how the skill handles them; prefer temporary or read-only test credentials. 3) The SKILL.md says charts are saved to D: by default — verify or change the output directory to a location appropriate for your system. 4) Test the skill first with non-sensitive/sample data to confirm behavior. 5) If you need guarantees about credential storage or network access, request additional documentation from the author (how credentials are provided, whether data is sent to external endpoints, and how outputs are stored).
功能分析
Type: OpenClaw Skill Name: jw-data-analyst Version: 1.0.0 The skill bundle contains only metadata and documentation for a data analysis assistant. The SKILL.md file describes standard data processing, statistical analysis, and visualization capabilities using common Python libraries like pandas and matplotlib. No executable code, suspicious network calls, or malicious prompt instructions were found.
能力评估
Purpose & Capability
The SKILL.md describes a reasonably-scoped data analysis tool (Excel/CSV/JSON/db/API → cleaning, stats, charts). However the package metadata contains an ownerId that differs from the registry metadata provided (inconsistent ownerId in _meta.json). Also the SKILL.md hardcodes a default save location ("默认保存到D盘") which is an unexpected assumption about the host environment and may not apply on non-Windows systems.
Instruction Scope
Instructions are high-level and focus on reading user-specified data sources and producing reports/plots; they do not instruct the agent to read arbitrary system files or exfiltrate data. Still, support for databases and API sources implies the skill will need connection credentials at runtime, but the SKILL.md does not specify how credentials are provided or handled. The hardcoded save-to-D: path is an unexpected I/O instruction that could cause write attempts to an inappropriate location.
Install Mechanism
No install spec and no code files — instruction-only — so nothing is written to disk by an installer. This is the lowest-risk install model.
Credentials
The skill declares no required environment variables, which is consistent for an instruction-only tool. However, because it supports SQLite/MySQL/PostgreSQL and API data sources, it will likely ask users for connection strings/credentials at runtime. The SKILL.md does not document how credentials should be supplied or stored, which raises a proportionality/usability question and a potential risk if users paste production credentials without guidance.
Persistence & Privilege
always:false and normal model invocation settings — the skill won't be force-included or request persistent elevated privileges. The skill does assert default file save behavior but does not attempt to modify other skills or system-wide settings.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install jw-data-analyst
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /jw-data-analyst 触发
  4. 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: Data analysis assistant for Excel/CSV/JSON/DB
元数据
Slug jw-data-analyst
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

JW Data Analyst 是什么?

数据分析助手 - 自动生成Python数据处理脚本、可视化图表、统计报告。支持Excel/CSV/JSON/数据库。觸發詞:数据分析、图表、统计、报表、可视化。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 76 次。

如何安装 JW Data Analyst?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install jw-data-analyst」即可一键安装,无需额外配置。

JW Data Analyst 是免费的吗?

是的,JW Data Analyst 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

JW Data Analyst 支持哪些平台?

JW Data Analyst 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 JW Data Analyst?

由 a85012712(@a85012712)开发并维护,当前版本 v1.0.0。

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