pr-description

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Repository: chdb-io/chdb
Last source activity: September 17, 2026 at 08:32
Detected SKILL.md language: English
Stars: 2,918
Forks: 137

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name: pr-description
description: Draft or update a pull request title and description for the current repository. Use when preparing, creating, or editing a pull request.

# Pull Request Description Inspect the diff against the base branch and the included commits before writing. ## Title - Use a concise, specific, capitalized imperative. - Describe the outcome rather than the implementation mechanism. - Do not use Conventional Commit prefixes such as `feat:` or `fix:`. ## Body - Explain what changed, why it changed, and its impact. - Link related issues when they are known. - List only validation that was actually run, including the result. - Mention breaking changes, limitations, or important reviewer context when applicable. Do not invent behavior, test results, or issue links. Create or edit a remote pull request only when the user explicitly asks.

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chdb-datastore

Use when the user has tabular data (pandas DataFrame, parquet, csv, Arrow, json) and wants to filter, group, aggregate, join, or speed up slow pandas. Provides chDB DataStore — same pandas API, ClickHouse engine underneath. Also handles reading from S3, MySQL, PostgreSQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake as DataFrames and joining across sources. TRIGGER when: user mentions DataFrame, parquet, csv, "fast pandas", "speed up pandas", or cross-source DataFrame joins; user imports `chdb.datastore` or `from datastore import DataStore`. SKIP this skill for raw SQL syntax (use chdb-sql instead), ClickHouse server administration, or non-Python DataStore API work.

2026-06-29

chdb-sql

Use when the user wants to run SQL — especially analytical SQL — on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake) without setting up a server. Provides chDB — embedded ClickHouse SQL in Python with 1000+ functions, Session for stateful multi-step pipelines, parametrized queries, and cross-source joins via `s3()`, `mysql()`, `postgresql()`, `iceberg()`, `deltaLake()`, `remoteSecure()` table functions. TRIGGER when: user wants SQL on parquet/csv/files or across remote analytical sources; uses ClickHouse SQL features (window functions, windowFunnel, geoToH3, JSON path ops, Session, parametrized queries); imports `chdb` or calls `chdb.query()`. SKIP this skill for pandas-style DataFrame method-chaining (use chdb-datastore instead) or ClickHouse server administration.

2026-06-29

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