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Found 7 Skills
Use when you need to reduce token usage, lower API cost, fit work within a context window, or speed up an expensive/slow agent loop. Triggers on phrases like "optimize tokens", "reduce token usage", "save on cost", "fit in context", "context too long", "running out of tokens", "prompt caching", "compact the context", "agent is too expensive", "shrink the prompt", "cheaper model", "tokens-per-task". Provides a layered tactic catalog — measurement (heuristic counting and budget allocation), prompt-side levers (caching, system-prompt diet, tool-definition pruning), context management (compression, observation masking, file-system offload), agent-loop patterns (parallel tool calls, batch operations, model routing by complexity), and output-side controls (depth tiers, stop sequences, structured output). Project-agnostic and provider-agnostic; works across Claude Code, Codex CLI, Cursor, Gemini CLI, and Copilot.
This skill should be used when the user wants to "write agent code", "build an agent with ADK", "add a tool", "create a callback", "define an agent", "use state management", or needs ADK (Agent Development Kit) Python API patterns and code examples. Part of the Google ADK skills suite. It provides a quick reference for agent types, tool definitions, orchestration patterns, callbacks, and state management. Do NOT use for creating new projects (use google-agents-cli-scaffold) or deployment (use google-agents-cli-deploy).
Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling
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.
Comprehensive guide to AI SDK v6 for agent development, tool definitions, multi-step agentic workflows, and result extraction patterns
Guide for giving your AI agents capabilities through tools. Helps you identify what your AI needs to do, create tool definitions, and attach them in a way that makes sense for your framework.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.