数据分析(DuckDB)
SkillDatabases & dataAnalyzes user-uploaded CSV/JSON data files using DuckDB (overview statistics or SQL queries), producing a results file.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the 数据分析(DuckDB) skill
What this skill tells your AI
The instructions your AI receives, as published by yrris/pro-agent in cognition/runtime/skills/data-analysis/SKILL.md and read by ahel’s review.
分析用户本轮上传的数据文件(CSV/JSON)。上传的文件名见消息中的〔用户上传附件〕注记。
用法
调用 script_runner:
script_runner(
skill="data-analysis",
script="analyze.py",
input_files=["sales.csv"], # 用户上传附件的文件名(必填)
script_args={
"files": ["sales.csv"], # 参与分析的文件(同 input_files)
"mode": "summary", # summary=概览(默认)| query=执行 SQL
"sql": "SELECT 类别, SUM(金额) FROM sales GROUP BY 类别" # mode=query 时必填
}
)
- 视图名 = 文件名去扩展名(
sales.csv→ 表sales;含特殊字符时用双引号包裹)。 mode=summary:每个文件输出行数、列名/类型、数值列统计(min/max/avg)、前 5 行样例。mode=query:执行任意 DuckDB SQL(SELECT),结果写result.csv;同时产出analysis.md报告。- 仅支持 CSV/JSON;Excel 请让用户转存 CSV 后再传。
产出
analysis.md:可读的分析报告(自动登记为可下载产物)。result.csv:query 模式的结果数据。
先跑 summary 了解数据结构,再写 SQL——不要凭空猜列名。
Signals
- GitHub stars
- 23
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
data-analysis-yrris- Source
- github.com/yrris/pro-agent