Loading...
Loading...
Found 128 Skills
Build AI agents for real-time financial options analysis with LangGraph, ChromaDB RAG, and Polygon.io data
Build a custom durable AI agent with full control over streamText options, provider configs, and tool loops. Compatible with the Workflow Development Kit.
Use when working with AWS Strands Agents SDK or Amazon Bedrock AgentCore platform for building AI agents. Provides architecture guidance, implementation patterns, deployment strategies, observability, quality evaluations, multi-agent orchestration, and MCP server integration.
Use when creating new skills, editing existing skills, auditing skill quality, or verifying skills before deployment. Triggers include skill authoring requests, skill review needs, or "the skill doesn't work" complaints.
Interactive tutorial that guides engineers through building their own coding agent (agentic loop) from scratch using raw HTTP calls to an LLM API. Supports Gemini, OpenAI (and compatible endpoints), and Anthropic. Supports TypeScript, Python, Go, and Ruby. Detects progress automatically. Use when someone says "build an agent", "teach me agents", or "/build-agent".
Agent Skill creation workflow. Use when creating new reusable AI agent skills, scaffolding skill directories, or converting existing guides into the portable Agent Skills standard format.
Complete Google Gemini API reference for 2026. Use whenever writing code that calls Gemini models. Covers the google-genai SDK, Gemini 3/3.1 models, thought signatures, thinking config, Interactions API, File Search (managed RAG), Computer Use, URL Context, Nano Banana image gen, Live API, ephemeral tokens, TTS, Veo video gen, Lyria music gen, and all tools. ALWAYS prefer `from google import genai` over any legacy import. Use this skill for ANY Gemini API question, even simple ones.
Create a new skill. When to use: When the user says "create skill", "new skill", "add skill", "initialize skill".
Build AI agents with in-process agent loops using Anthropic or OpenAI APIs, custom tools, MCP servers, and multi-turn conversations
Implementation guide for 17+ agentic AI architectures using LangChain and LangGraph for building sophisticated AI agents
Replace with a trigger-style description of when this skill should activate. Be specific — this is what the agent uses to decide whether to load the skill. Example: "Sui TypeScript SDK integration. Use when writing, reviewing, or debugging TypeScript code that interacts with Sui RPCs, transactions, or on-chain state."
Amazon Bedrock Agents for building autonomous AI agents with foundation model orchestration, action groups, knowledge bases, and session management. Use when creating AI agents, orchestrating multi-step workflows, integrating tools with LLMs, building conversational agents, implementing RAG patterns, managing agent sessions, deploying production agents, or connecting knowledge bases to agents.