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Found 2,040 Skills
Provides Complete patterns for testing async Python code with pytest: pytest-asyncio configuration, AsyncMock usage, async fixtures, testing FastAPI with AsyncClient, testing Kafka async producers/consumers, event loop and cleanup patterns. Use when: Testing async functions, async use cases, FastAPI endpoints, async database operations, Kafka async clients, or any async/await code patterns.
Detects orphaned code (files/functions that exist but are never imported or called in production), preventing "created but not integrated" failures. Use before marking features complete, before moving ADRs to completed, during code reviews, or as part of quality gates. Triggers on "detect orphaned code", "find dead code", "check for unused modules", "verify integration", or proactively before completion. Works with Python modules, functions, classes, and LangGraph nodes. Catches the ADR-013 failure pattern where code exists and tests pass but is never integrated.
创建高质量 MCP（模型上下文协议）服务器的指南，使 LLM 能够通过精心设计的工具与外部服务交互。在构建 MCP 服务器以集成外部 API 或服务时使用，无论是 Python (FastMCP) 还是 Node/TypeScript (MCP SDK)。
Best practices for developing tools, dashboards and interactive data apps with HoloViz Panel. Create reactive, component-based UIs with widgets, layouts, templates, and real-time updates. Use when developing interactive data exploration tools, dashboards, data apps, or any interactive Python web application. Supports file uploads, streaming data, multi-page apps, and integration with HoloViews, hvPlot, Pandas, Polars, DuckDB and the rest of the HoloViz and PyData ecosystems.
Use when adding LangChain-based LLM routes or services in Python or Next.js stacks; pair with architect-stack-selector.
4 production-ready business and growth skills: customer success manager with health scoring and churn prediction, sales engineer with RFP analysis, revenue operations with pipeline and GTM metrics, and contract & proposal writer. Python tools included (all stdlib-only). Works with Claude Code, Codex CLI, and OpenClaw.
Use when the user wants Codex to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to Codex without changing the generated Python harness format.
Use this skill when working with the mcp-skill CLI to create generated MCP app wrappers, list available generated apps, list functions for a specific app, inspect a generated function signature and docstring, or understand how to call generated apps from async Python.
This skill should be used when the user asks to "use NumPy", "write NumPy code", "optimize NumPy arrays", "vectorize with NumPy", or needs guidance on NumPy best practices, array operations, broadcasting, memory management, or scientific computing with Python.
This skill should be used when the user asks to "build an AI agent with Claude", "use the Claude Agent SDK", "integrate claude-agent-sdk into a project", "set up an autonomous agent with tools", or needs guidance on the Anthropic Claude Agent SDK best practices for Python and TypeScript.
Better Harness Tools for Claude Code — a Python (and in-progress Rust) rewrite of the Claude Code agent harness, with CLI tooling for manifest inspection, parity auditing, and tool/command inventory.
Agent skill to convert any arxiv paper into a citation-anchored, working Python implementation with ambiguity auditing