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Found 1,282 Skills
Creates product strategies using Crossing the Chasm, Playing to Win, and strategic canvas frameworks. Use when defining where to play and how to win, choosing beachhead markets, or connecting tactics to strategy.
Use this skill when building MCP (Model Context Protocol) servers with FastMCP in Python. FastMCP is a framework for creating servers that expose tools, resources, and prompts to LLMs like Claude. The skill covers server creation, tool/resource definitions, storage backends (memory/disk/Redis/DynamoDB), server lifespans, middleware system (8 built-in types), server composition (import/mount), OAuth Proxy, authentication patterns, icons, OpenAPI integration, client configuration, cloud deployment (FastMCP Cloud), error handling, and production patterns. It prevents 25+ common errors including storage misconfiguration, lifespan issues, middleware order errors, circular imports, module-level server issues, async/await confusion, OAuth security vulnerabilities, and cloud deployment failures. Includes templates for basic servers, storage backends, middleware, server composition, OAuth proxy, API integrations, testing, and self-contained production architectures. Keywords: FastMCP, MCP server Python, Model Context Protocol Python, fastmcp framework, mcp tools, mcp resources, mcp prompts, fastmcp storage, fastmcp memory storage, fastmcp disk storage, fastmcp redis, fastmcp dynamodb, fastmcp lifespan, fastmcp middleware, fastmcp oauth proxy, server composition mcp, fastmcp import, fastmcp mount, fastmcp cloud, fastmcp deployment, mcp authentication, fastmcp icons, openapi mcp, claude mcp server, fastmcp testing, storage misconfiguration, lifespan issues, middleware order, circular imports, module-level server, async await mcp
Design effective system prompts for custom agents. Use when creating agent system prompts, defining agent identity and rules, or designing high-impact prompts that shape agent behavior.
When a user is stuck, frustrated, or describing a problem vaguely, do NOT immediately suggest solutions. First, force structured problem articulation through targeted questions: What did you expect? What happened instead? What have you tried? Only after the problem is clearly defined, propose solutions.
Comprehensive package and environment management using pixi - a fast, modern, cross-platform package manager. Use when working with pixi projects for (1) Project initialization and configuration, (2) Package management (adding, removing, updating conda/PyPI packages), (3) Environment management (creating, activating, managing multiple environments), (4) Feature management (defining and composing feature sets), (5) Task execution and management, (6) Global tool installation, (7) Dependency resolution and lock file management, or any other pixi-related operations. Supports Python, C++, R, Rust, Node.js and other languages via conda-forge ecosystem.
Expert C4 Component-level documentation specialist. Synthesizes C4 Code-level documentation into Component-level architecture, defining component boundaries, interfaces, and relationships. Creates component diagrams and documentation. Use when synthesizing code-level documentation into logical components.
Define and run Eve pipelines and workflows via manifest and CLI. Use when wiring build, release, deploy flows or invoking workflow jobs.
Strategic planning for Product Hunt launches. Use this skill when you need to define launch objectives, create a preparation timeline, or develop an overall launch strategy. Helps with goal-setting, timeline creation, and strategic decision-making.
Structure stories around essential emotional moments using Rodriguez's approach integrated with elemental genres. Use when plotting feels mechanical, when emotional beats need defining, or when building stories from vivid scenes rather than plot outlines.
Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.
Use when creating or editing Obsidian Bases (.base files) that define views, filters, formulas, or summaries for note collections.
Requirements clarification and decomposition, identify stakeholders and label requirement items with their corresponding owners and business entities; only produce structured requirement descriptions without modeling definitions, which can be used as input for subsequent modeling