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Found 7,061 Skills
Search across company knowledge with the Glean CLI. Use when finding documents, policies, engineering docs, or any information across enterprise data sources.
WeCom meeting management skill, which supports canceling meetings and updating meeting invited members. It is triggered when users need to "cancel a meeting", "delete a meeting", "modify meeting members", "add meeting participants", or "remove meeting members".
WeCom to-do list query skill, which supports filtering by creation time and reminder time, as well as pagination. It is applicable to scenarios where users need to browse the to-do overview, such as when they say "Check my to-do list", "What to-dos do I have", "What are my to-dos this week", "What to-dos are there recently", "Check my to-dos", "List all to-dos", etc. Note: This skill only returns to-do summary information (excluding content and assignees). If you need complete details, please use it together with wecomcli-get-todo-detail.
Sync, search, classify, and query X/Twitter bookmarks locally using the Field Theory CLI
Search across company knowledge with the Glean CLI. Use when finding documents, policies, engineering docs, or any information across enterprise data sources.
Chat with Glean Assistant from the command line. Use when asking questions, summarizing documents, or getting AI-powered answers about company knowledge.
Retrieve, summarize, and inspect documents indexed by Glean. Use when getting document content, summaries, permissions, or metadata by URL.
Use mmx to generate text, images, video, speech, and music via the MiniMax AI platform. Use when the user wants to create media content, chat with MiniMax models, perform web search, or manage MiniMax API resources from the terminal.
Complete Polygon agent CLI. Session-based smart contract wallets (Sequence), token ops (send/swap/bridge/deposit via Trails), ERC-8004 on-chain identity + reputation, x402 micropayments. Single CLI entry point, AES-256-GCM encrypted storage.
Use when the user asks about the Alpic CLI (`alpic`) — deploying MCP servers, viewing logs, debugging deployments, managing environment variables, configuring the playground, connecting git, and publishing to the MCP Registry.
Drop-in pandas replacement with ClickHouse performance. Use `import chdb.datastore as pd` (or `from datastore import DataStore`) and write standard pandas code — same API, 10-100x faster on large datasets. Supports 16+ data sources (MySQL, PostgreSQL, S3, MongoDB, ClickHouse, Iceberg, Delta Lake, etc.) and 10+ file formats (Parquet, CSV, JSON, Arrow, ORC, etc.) with cross-source joins. Use this skill when the user wants to analyze data with pandas-style syntax, speed up slow pandas code, query remote databases or cloud storage as DataFrames, or join data across different sources — even if they don't explicitly mention chdb or DataStore. Do NOT use for raw SQL queries, ClickHouse server administration, or non-Python languages.
In-process ClickHouse SQL engine for Python — run ClickHouse SQL queries directly on local files, remote databases, and cloud storage without a server. Use when the user wants to write SQL queries against Parquet/CSV/ JSON files, use ClickHouse table functions (mysql(), s3(), postgresql(), iceberg(), deltaLake() etc.), build stateful analytical pipelines with Session, use parametrized queries, window functions, or other advanced ClickHouse SQL features. Also use when the user explicitly mentions chdb.query(), ClickHouse SQL syntax, or wants cross-source SQL joins. Do NOT use for pandas-style DataFrame operations — use chdb-datastore instead.