Loading...
Loading...
Found 1,213 Skills
Diagnose and improve marketplace liquidity (match rate/fill rate, time-to-match, reliability) by segment. Produces a Marketplace Liquidity Management Pack: liquidity definition + metric tree, fragmentation map, segment scorecard, supply/demand bottleneck diagnosis, experiment backlog, measurement plan, and operating cadence. Use for Growth teams running two-sided marketplaces.
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.
Expert growth product management guidance for SaaS applications. Use when designing growth loops, optimizing activation and onboarding, building retention systems, creating referral mechanics, running growth experiments, defining north star metrics, or implementing PLG strategies. Covers the full growth lifecycle from acquisition to monetization.
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.
One-stop creation of SecondMe integration projects, executing initialization, requirement definition, and project generation in sequence
Master product strategy, market analysis, competitive positioning, and long-term product vision. Define business models and craft go-to-market strategies that drive success.
Integrate Siri voice interactions, Shortcuts, and intelligent suggestions into iOS/watchOS apps using Apple's SiriKit framework. Use when implementing Intents extensions, custom intents, Siri Shortcuts, voice phrase handling, intent resolution/confirmation/handling, IntentsUI for custom Siri interfaces, donating shortcuts, or App Intents migration. Covers system intent domains (messaging, payments, ride booking, workouts, media) and custom intent definition.
Tinybird TypeScript SDK for defining datasources, pipes, and queries with full type inference. Use when working with @tinybirdco/sdk, TypeScript Tinybird projects, or type-safe data ingestion and queries.
Create a structured problem statement document for a feature, bugfix, or project. Use when starting a project, adding a feature, or fixing a bug and you need to clearly define the problem, context, desired outcome, and success criteria. Accepts input from Jira tickets (via MCP), document links, or text descriptions.
Fuzzing skill for automated input-driven bug finding in C/C++. Use when setting up libFuzzer or AFL++ fuzz targets, defining fuzz entry points around parsing or I/O boundaries, integrating fuzzing into CI, managing corpora, or combining fuzzing with sanitizers. Activates on queries about libFuzzer, AFL, afl-fuzz, fuzz targets, corpus management, coverage-guided fuzzing, or OSS-Fuzz integration.
Turn rough ideas into structured, validated idea documents through collaborative dialogue. Explores context, asks clarifying questions one at a time, proposes alternative approaches with feasibility evaluation, and produces documents ready for requirements definition. Use when: "ideation", "brainstorm", "new idea", "explore an idea", "I want to build", "what if we", "let's think about", "propose approaches", "evaluate this idea", "idea document", "アイデア出し", "案出し", "ブレスト", "アイデアを整理", "検討したい".