Bloblang Authoring

Python 的进程内 ClickHouse SQL 引擎 — 无需服务器即可直接在本地文件、远程数据库和云存储上运行 ClickHouse SQL 查询。当用户希望针对 Parquet/CSV/JSON 文件编写 SQL 查询、使用 ClickHouse 表函数（如 mysql()、s3()、postgresql()、iceberg()、deltaLake() 等）、使用 Session 构建有状态的分析管道、使用参数化查询、窗口函数或其他高级 ClickHouse SQL 功能时使用。当用户明确提及 chdb.query()、ClickHouse SQL 语法或希望进行跨源 SQL 连接时也请使用。请勿用于 pandas 风格的 DataFrame 操作 — 请改用 chdb-datastore。

Serialize and deserialize data across common formats including JSON, XML, YAML, Protocol Buffers, MessagePack, and Apache Arrow/Parquet. Covers format selection criteria, encoding/decoding patterns, performance trade-offs, and interoperability considerations. Use when choosing a wire format for API communication, persisting structured data to disk, exchanging data between systems written in different languages, optimizing transfer size or parsing speed, or migrating from one serialization format to another.

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

Generate CSV, Markdown, and XLSX spreadsheets from structured tabular data.

Use this skill whenever the user mentions IP geolocation feeds, RFC 8805, geofeeds, or wants help creating, tuning, validating, or publishing a self-published IP geolocation feed in CSV format. Intended user audience is a network operator, ISP, mobile carrier, cloud provider, hosting company, IXP, or satellite provider asking about IP geolocation accuracy, or geofeed authoring best practices. Helps create, refine, and improve CSV-format IP geolocation feeds with opinionated recommendations beyond RFC 8805 compliance. Do NOT use for private or internal IP address management — applies only to publicly routable IP addresses.

Extract typed JSON from public website pages using a schema.