为 Datadata 平台编写 DQL 数据处理脚本 — 基于 Starlark 的扩展脚本语言，支持 DataFrame/Series 操作、SQL 查询、HTTP 请求等。当用户需要编写数据转换、数据清洗、数据生成或自定义数据处理逻辑时使用此 skill。
/plugin marketplace add datadata-team/datadata-skills
The exact command may vary by repository. Check the README on GitHub.
For the skill author
Shows your skill is listed on Skillteca, generates a backlink and trackable traffic.
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Use this skill for any task involving spreadsheet files as primary input or output, such as opening, reading, editing, fixing, creating, or converting .xlsx, .xlsm, .csv, or .tsv files.
Searches claude-mem's persistent cross-session memory database. Use this to answer questions about previous solutions or retrieve work from past sessions.
Generates a week-by-week narrative digest of a project's Claude-mem timeline, splitting it into ISO-week files and using subagents to produce weekly chapters. Ideal for "weekly digests" or "narrative chapters" of a project's history.
This skill explains how claude-mem captures observations, when memory injection occurs, and where its data is stored.
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DQL 是基于 Starlark 的自定义脚本语言，扩展了 Starlark 的语法和标准库，提供数据处理、HTTP 网络调用等能力。
return 语句DQL 脚本实际是一个函数的 body，最后必须有 return 语句返回数据，否则执行结果为空。
# ✅ 正确
df = query("SELECT * FROM users")
return df
# ❌ 错误：没有 return，结果为空
df = query("SELECT * FROM users")
禁止仅凭本文档就编写 DQL 代码。 本文档只是索引，实际 API 签名、参数、返回值以 references 为准。编写代码前至少阅读以下对应文档：
| 场景 | 必读文档
[Description truncada. Veja o README completo no GitHub.]
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