ADK Skill

An Agent Skill for building single-agent and multi-agent systems with Google’s Agent Development Kit (ADK) in Python, Java, Go, Kotlin, and TypeScript. Skill 2.2.0, verified against ADK Python 2.13.0 on 2026-10-25. Covers graph/dynamic workflows, collaboration, cancellation, approvals, tools, memory, evaluation and deployment. Python examples require Python 3.11+; API availability and experimental status are specific to each SDK.

This skill gives your coding agent deep knowledge of ADK architecture, patterns, and best practices — covering workflow types, tools, callbacks, state management, memory, artifacts, multi-agent orchestration, testing, evaluation, and deployment across all supported languages.

See release notes for version 2.2.0, compatibility changes and verification limits. Contributor and agent instructions live in AGENTS.md; the update’s phase record is in tasks.md.

What’s Included

adk-skill/
├── SKILL.md                          # Core instructions (under 500 lines)
└── references/
    ├── a2a-protocol.md               # A2A protocol: expose, consume, agent cards
    ├── advanced-patterns.md          # Multi-agent, App config, Agent Config, Visual Builder, AG-UI, streaming, multi-model
    ├── design-patterns.md            # Agent design patterns & best practices
    ├── evaluation.md                 # Quality/efficiency metrics, multi-turn evaluator, user simulation
    ├── memory-artifacts.md           # In-memory/SQLite/Vertex/MongoDB memory, versioned artifacts
    ├── multi-language.md             # Java, Go, Kotlin, TypeScript patterns
    ├── tools-reference.md            # FunctionTool, MCP, Toolbox, RAG, SkillToolset, OpenAPI, tool auth, confirmations
    ├── troubleshooting.md            # Common errors, debugging, 1.x→2.0 migration, performance tips
    └── workflows.md                  # Graph-based routing, dynamic workflows, HITL, parallel, custom IDs

SKILL.md covers project structure, all 4 workflow types (Graph-based Workflow, Dynamic @node, Collaborative with mode, Template SequentialAgent/ParallelAgent/LoopAgent), function tools, OpenAPI tools, AgentTool, MCP integration, agent-as-MCP-server (to_mcp_server), A2A remote agents, memory service, artifacts, callbacks, state management with Jinja2 instruction templating, structured output, testing with InMemoryRunner, YAML-based Agent Config, model selection (gemini-3.5-flash default), design patterns with key rules, decision guides, and links to external documentation.

Reference files provide advanced patterns loaded on demand: