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Found 1,152 Skills
AI agent patterns with Trigger.dev - orchestration, parallelization, routing, evaluator-optimizer, and human-in-the-loop. Use when building LLM-powered tasks that need parallel workers, approval gates, tool calling, or multi-step agent workflows.
Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
AWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services. Use when working with Gateway, Runtime, Memory, Identity, or any AgentCore component. Covers MCP target deployment, credential management, schema optimization, runtime configuration, memory management, and identity services.
This skill should be used when the user needs to automate multi-step website tasks. Activates for browser automation, web scraping, UI testing, or building AI agents. Provides complete action manuals with step-by-step instructions and verified selectors.
Bootstrap a modular AI agent with OpenRouter SDK, extensible hooks, and optional Ink TUI
Give AI agents their own email inboxes using the AgentMail API. Use when building email agents, sending/receiving emails programmatically, managing inboxes, handling attachments, organizing with labels, creating drafts for human approval, or setting up real-time notifications via webhooks/websockets. Supports multi-tenant isolation with pods.
Complete Valyu API toolkit for AI agents. Use this skill when asked to perform real-time search across web, academic, medical, transportation, financial sources, content extraction from URLs, AI-powered answers with citations, or comprehensive deep research reports.
Query blockchain data across 40+ chains, create AI agents for crypto analytics, and build automated data pipelines. Use when working with blockchain data, crypto wallets, DeFi protocols, NFTs, token transfers, or on-chain analytics. Requires the Flipside CLI (https://docs.flipsidecrypto.xyz/get-started/cli).
LangChain LLM application framework with chains, agents, RAG, and memory for building AI-powered applications
Tool and function calling patterns with LangChain4j. Define tools, handle function calls, and integrate with LLM agents. Use when building agentic applications that interact with tools.
Full-featured Agent Skills management: Search 35+ skills, install locally, star favorites, update from sources. Use when looking for skills, installing new skills, or managing your skill collection.
Integrate Honcho memory and social cognition into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, or implementing the dialectic chat endpoint for AI agents.