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Handles Memos API usage: crafting curl/python requests with Authorization Bearer tokens, paginating with pageSize/pageToken, using filter (AIP-160 syntax), updateMask updates, and mapping common endpoints (memo CRUD, attachments, activities, auth, identity providers). Trigger when user asks to call/inspect/troubleshoot Memos API, generate sample requests, or batch download memos. Warn to avoid printing tokens.
使用 Python + UV 读写小红书（XHS）数据的技能，仅依赖 httpx + pycryptodome， 通过 browser_use get_cookies 自动获取 Cookie 完成认证，无需手动复制。 支持搜索笔记/用户/话题、读取笔记详情与评论、推荐 Feed、热门榜单、 社交操作（关注/收藏）、互动（点赞/评论/回复）、通知查询、创作者笔记管理等。 当用户提到"小红书"、"XHS"、"抓取小红书"、"搜索小红书笔记"、"小红书评论"、 "xiaohongshu-hub"、"读取小红书数据"、"小红书 Cookie"， 或任何需要以编程方式读写小红书内容的场景，必须触发本技能。
Extracts, transforms, and analyzes NBA statistics using the nba_api Python library. Use when working with NBA player stats, team data, game logs, shot charts, league statistics, or any NBA-related data engineering tasks. Supports both stats.nba.com endpoints and static player/team lookups.
Python dataclass best practices: slots, frozen, validation. Trigger when optimizing dataclasses or creating config classes.
Helps work with the b00t datum system - TOML-based configuration for AI models, providers, and services. Datums are stored in ~/.dotfiles/_b00t_/ and specify WHICH environment variables are required (not the values). Enables DRY approach by centralizing configuration in Rust, exposed to Python via PyO3.
Implement a Python connector that conforms to the LakeflowConnect interface for data ingestion.
Master machine learning, data engineering, AI engineering, LLMs, prompt engineering, and MLOps. Build intelligent systems with Python.
Use when creating database migrations. Prevents data loss, downtime, and performance issues. Supports PostgreSQL, MySQL, SQLite. Python 3.8+
Apply Grey Haven database conventions - snake_case fields, multi-tenant with tenant_id and RLS, proper indexing, migrations for Drizzle (TypeScript) and SQLModel (Python). Use when designing schemas, writing database code, creating migrations, setting up RLS policies, or when user mentions 'database', 'schema', 'Drizzle', 'SQLModel', 'migration', 'RLS', 'tenant_id', 'snake_case', 'indexes', or 'foreign keys'.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Use this agent when you need to design, implement, or optimize FastAPI backend applications. This includes API endpoint creation, database integration, authentication/authorization implementation, cloud deployment strategies, business logic architecture, performance optimization, and following FastAPI best practices.
Generate .agents.yml config from user answers. Provides tech stack templates for Rails, Python, Node, and Generic projects.
Writing Datasette plugins using Python and the pluggy plugin system. Use when Claude needs to: (1) Create a new Datasette plugin, (2) Implement plugin hooks like prepare_connection, register_routes, render_cell, etc., (3) Add custom SQL functions, (4) Create custom output renderers, (5) Add authentication or permissions logic, (6) Extend Datasette's UI with menus, actions, or templates, (7) Package a plugin for distribution on PyPI
Generate Docker Compose and Dockerfile configurations for local development through interactive Q&A. Supports PHP/Laravel, WordPress, Drupal, Joomla, Node.js, and Python stacks with Nginx, Supervisor/PM2, databases, Redis, and email testing. Always asks clarifying questions before generating configurations.
Python interoperability setup using libpython-clj for Clojure agent development. Includes Python environment configuration, module importing strategies, data type conversion between Python and Clojure, NumPy/Pandas/HuggingFace integration, virtual environment setup, and performance optimization. Use when integrating Python ML libraries, setting up data science workflows, troubleshooting Python interop issues, working with NumPy arrays or Pandas DataFrames, or calling HuggingFace transformers from Clojure.
Troubleshoot and resolve issues with Azure Messaging SDKs for Event Hubs and Service Bus. Covers connection failures, authentication errors, message processing issues, and SDK configuration problems. WHEN: event hub SDK error, service bus SDK issue, messaging connection failure, AMQP error, event processor host issue, message lock lost, message lock expired, lock renewal, lock renewal batch, send timeout, receiver disconnected, SDK troubleshooting, azure messaging SDK, event hub consumer, service bus queue issue, topic subscription error, enable logging event hub, service bus logging, eventhub python, servicebus java, eventhub javascript, servicebus dotnet, event hub checkpoint, event hub not receiving messages, service bus dead letter, batch processing lock, session lock expired, idle timeout, connection inactive, link detach, slow reconnect, session error, duplicate events, offset reset, receive batch.
Work with TON blockchain via the tonapi Python SDK — query accounts, transactions, jettons, NFTs, staking, DNS, emulate messages, subscribe to real-time events, and manage webhooks. Use this skill whenever the user mentions TONAPI, tonapi.io, TON blockchain data, wallet balance, jetton transfers, NFT collections, or wants to interact with TON via TONAPI. Also use when the user works with code that imports from pytonapi.rest, pytonapi.streaming, pytonapi.webhook, or pytonapi.types, or asks about TONAPI endpoints, even if they don't explicitly mention "pytonapi".
Vast.ai Python SDK — high-level API for GPU instances, volumes, serverless endpoints, and billing.
Release AutoWSGR Python backend to PyPI and GitHub. USE WHEN: bumping backend version, publishing to PyPI, creating backend release, tagging backend build. Includes mandatory local CI check before push.
Create and publish distributable scientific Python packages following Scientific Python community best practices. Covers pyproject.toml, src layout, Hatchling, metadata, CLI entry points, and PyPI publishing.
