google-adk

name

google-adk

description

ALWAYS use this skill for any question involving Google ADK (Agent Development Kit). This includes: building or configuring agents (LlmAgent, SequentialAgent, LoopAgent, ParallelAgent, custom BaseAgent), writing function tools or connecting MCP/OpenAPI tools, managing sessions/state/memory, multi-agent routing and pipelines, before/after callbacks, streaming with Gemini Live API (run_live, LiveRequestQueue), deploying to Cloud Run or Vertex AI Agent Engine, evaluating agent behavior, A2A protocol, context caching/compression, grounding with Google Search. Trigger on any mention of 'adk', 'google adk', 'agent development kit', 'LlmAgent', 'SequentialAgent', 'LoopAgent', 'AgentTool', 'tool_context', 'InMemorySessionService', 'VertexAiSessionService', or related ADK class/API names — even if the user doesn't call it ADK explicitly.

Google ADK

Comprehensive reference for Google's Agent Development Kit. Use this skill when:

• Creating or configuring any ADK agent (LlmAgent, SequentialAgent, LoopAgent, ParallelAgent, custom agents)
• Wiring tools to agents (function tools, built-in tools, MCP, OpenAPI, tool authentication)
• Managing sessions, state, and memory
• Building multi-agent systems or agent pipelines
• Integrating the Gemini Live API or building streaming agents
• Deploying agents to Cloud Run, GKE, or Vertex AI Agent Engine
• Evaluating agent behavior or writing agent tests
• Using the A2A (Agent-to-Agent) protocol for inter-agent communication
• Configuring callbacks, grounding, context caching, or observability

How to Use This Skill

1. Identify the task from the Quick Reference table below
2. Load the concept reference file (prose, architecture, API parameters)
3. If you need runnable code, also load the matching language sidecar: filename-python.md, filename-typescript.md, filename-go.md, or filename-java.md

Language sidecar files exist for these 10 high-complexity references — load them alongside the parent when you need code examples:

Parent file	Python sidecar	TS sidecar	Go sidecar	Java sidecar
agents/llm-agents.md	agents/llm-agents-python.md	agents/llm-agents-typescript.md	agents/llm-agents-go.md	agents/llm-agents-java.md
agents/custom-agents.md	agents/custom-agents-python.md	agents/custom-agents-typescript.md	agents/custom-agents-go.md	agents/custom-agents-java.md
agents/multi-agent-systems.md	agents/multi-agent-systems-python.md	agents/multi-agent-systems-typescript.md	agents/multi-agent-systems-go.md	agents/multi-agent-systems-java.md
tools/function-tools-overview.md	tools/function-tools-overview-python.md	tools/function-tools-overview-typescript.md	tools/function-tools-overview-go.md	tools/function-tools-overview-java.md
tools/mcp-tools.md	tools/mcp-tools-python.md	tools/mcp-tools-typescript.md	tools/mcp-tools-go.md	tools/mcp-tools-java.md
tools/tool-authentication.md	tools/tool-authentication-python.md	tools/tool-authentication-typescript.md*	tools/tool-authentication-go.md*	tools/tool-authentication-java.md*
callbacks/types-of-callbacks.md	callbacks/types-of-callbacks-python.md	callbacks/types-of-callbacks-typescript.md	callbacks/types-of-callbacks-go.md	callbacks/types-of-callbacks-java.md
sessions/state.md	sessions/state-python.md	sessions/state-typescript.md	sessions/state-go.md	sessions/state-java.md
sessions/memory.md	sessions/memory-python.md	sessions/memory-typescript.md*	sessions/memory-go.md	sessions/memory-java.md
streaming/part1-intro-to-streaming.md	streaming/part1-intro-to-streaming-python.md	streaming/part1-intro-to-streaming-typescript.md*	streaming/part1-intro-to-streaming-go.md*	streaming/part1-intro-to-streaming-java.md*

* = stub only, source docs have no examples for this language yet

All sidecar files are under reference/ — prepend reference/ to the paths above.

---

Quick Reference: Common Tasks

Task	Load These References
Create a basic LLM agent	reference/getting-started/python-quickstart.md or typescript-quickstart.md / go-quickstart.md / java-quickstart.md
Understand LlmAgent parameters (name, model, tools, instructions, output_key)	reference/agents/llm-agents.md + language sidecar
Build a sequential pipeline of agents	reference/agents/workflow/sequential-agents.md
Build a loop / retry pattern	reference/agents/workflow/loop-agents.md
Run agents in parallel	reference/agents/workflow/parallel-agents.md
Build a multi-agent system with routing	reference/agents/multi-agent-systems.md + language sidecar
Create a custom agent (subclass BaseAgent)	reference/agents/custom-agents.md + language sidecar
Write a function tool with ADK patterns	reference/tools/function-tools-overview.md + language sidecar
Use LongRunningFunctionTool or AgentTool	reference/tools/function-tools-overview.md + language sidecar
Connect an MCP server as tools	reference/tools/mcp-tools.md + reference/tools/mcp-tools-python.md
Expose an OpenAPI spec as tools	reference/tools/openapi-tools.md
Add OAuth/API key auth to tools	reference/tools/tool-authentication.md + reference/tools/tool-authentication-python.md
Add human-in-the-loop confirmations	reference/tools/action-confirmations.md
See all built-in & third-party integrations	reference/tools/tools-and-integrations.md
Read/write session state, use state prefixes	reference/sessions/state.md + language sidecar
Use output_key to pass data between agents	reference/sessions/state.md + language sidecar
Use persistent sessions (DatabaseSessionService)	reference/sessions/sessions.md
Add long-term memory (MemoryService)	reference/sessions/memory.md + language sidecar
Add callbacks (before/after model/tool/agent)	reference/callbacks/types-of-callbacks.md + language sidecar
Callback patterns and best practices	reference/callbacks/callback-patterns.md
Configure models (Gemini, Claude, Vertex, Ollama, LiteLLM)	reference/models/models-overview.md
Use Claude (Anthropic) as the model	reference/models/claude.md
Use Vertex AI hosted models	reference/models/vertex-ai.md
Use Ollama / local models	reference/models/ollama.md
Build a streaming / realtime agent	reference/streaming/streaming-overview.md + reference/streaming/part1-intro-to-streaming.md + reference/streaming/part1-intro-to-streaming-python.md
Stream audio, images, or video	reference/streaming/part5-audio-images-video.md
Use Google Search grounding	reference/grounding/google-search-grounding.md
Use Vertex AI Search grounding	reference/grounding/vertex-ai-search-grounding.md
Work with artifacts (files, blobs)	reference/components/artifacts.md
Run the agent (CLI / web UI / API server)	reference/runtime/runtime-overview.md
Deploy to Cloud Run	reference/deployment/cloud-run.md
Deploy to Vertex AI Agent Engine	reference/deployment/agent-engine.md
Evaluate agent quality / write eval tests	reference/evaluation/evaluation-overview.md
Expose an agent via A2A protocol	reference/a2a/quickstart-exposing-python.md
Consume a remote agent via A2A	reference/a2a/quickstart-consuming-python.md
Enable tracing / logging / observability	reference/observability/observability-overview.md
Use context caching to reduce cost	reference/context/context-caching.md
Compress long context windows	reference/context/context-compression.md
CLI commands reference	reference/reference/cli-reference.md

---

1. Getting Started

Start here when beginning a new ADK project or when you need installation, quickstart, or conceptual overview.

Reference	When to Consult
reference/home.md	ADK high-level overview: what it is, key features, multi-language support
reference/getting-started/technical-overview.md	Architecture: agents, tools, sessions, events, runners — how they fit together
reference/getting-started/advanced-setup.md	Installation, virtual envs, CLI setup, API key config, optional dependencies
reference/getting-started/python-quickstart.md	First Python agent in 5 minutes
reference/getting-started/typescript-quickstart.md	First TypeScript agent in 5 minutes
reference/getting-started/go-quickstart.md	First Go agent in 5 minutes
reference/getting-started/java-quickstart.md	First Java agent in 5 minutes
reference/getting-started/quickstart-multi-tool-agent.md	Building an agent with multiple tools: weather + time + translation
reference/getting-started/tutorial-agent-team.md	Multi-agent tutorial: orchestrator + specialized sub-agents
reference/getting-started/quickstart-streaming-python.md	Getting started with streaming agents in Python
reference/getting-started/quickstart-streaming-java.md	Getting started with streaming agents in Java
reference/getting-started/coding-with-ai.md	Using AI assistants (Claude, Gemini, Cursor) to build ADK projects

---

2. Agents

Core agent types and configuration. Almost every ADK task starts here.

Reference	When to Consult
reference/agents/agents-overview.md	Overview of all agent types and when to use each
reference/agents/llm-agents.md	LlmAgent concepts: name, model, description, instructions, tools, output_key, planner, code_executor — load language sidecar for code
reference/agents/workflow-agents.md	Workflow agents overview: Sequential, Loop, Parallel — when and why
reference/agents/workflow/sequential-agents.md	SequentialAgent: chaining agents in order, passing context between steps
reference/agents/workflow/loop-agents.md	LoopAgent: iteration, stopping conditions, max_iterations
reference/agents/workflow/parallel-agents.md	ParallelAgent: concurrent execution, independent subtasks, fan-out patterns
reference/agents/custom-agents.md	BaseAgent subclassing: _run_async_impl, custom orchestration logic — load language sidecar for the StoryFlowAgent pattern
reference/agents/multi-agent-systems.md	Multi-agent coordination: sub_agents hierarchy, AgentTool, LLM transfer, shared state — load language sidecar for composition patterns
reference/agents/agent-config.md	Agent configuration file format (agentconfig.json)

---

3. Models

Configuring which LLM backs your agent.

Reference	When to Consult
reference/models/models-overview.md	All supported models, how to specify model strings, model selection guidance
reference/models/gemini.md	Google Gemini models (gemini-2.5-flash, gemini-2.0-flash, etc.), API keys, model IDs
reference/models/claude.md	Anthropic Claude models via API, supported model IDs, Python/TS/Go/Java setup
reference/models/vertex-ai.md	Models hosted on Vertex AI (Gemini, Claude, Llama, etc.) via Vertex endpoint
reference/models/apigee.md	Apigee AI Gateway for enterprise model routing and governance
reference/models/ollama.md	Ollama for local model inference: setup, model pull, connecting to ADK
reference/models/litellm.md	LiteLLM proxy: 100+ providers (OpenAI, Azure, Mistral, etc.) through one interface
reference/models/vllm.md	vLLM for high-throughput local inference
reference/models/litert-lm.md	LiteRT-LM for on-device inference on Android/embedded

---

4. Tools

Giving agents capabilities to act.

Reference	When to Consult
reference/tools/tools-and-integrations.md	All built-in tools (Google Search, code exec, etc.) and third-party integrations (LangChain, CrewAI, Vertex)
reference/tools/function-tools-overview.md	Writing custom function tools: type hints, docstrings, return types, async, long-running — load language sidecar for LongRunningFunctionTool and AgentTool patterns
reference/tools/tool-performance.md	Parallel tool calls, caching tool results, performance optimization
reference/tools/action-confirmations.md	Requiring human approval before tool execution
reference/tools/mcp-tools.md	Connecting MCP servers as ADK tools: MCPToolset, stdio and SSE transports — load Python sidecar for full wiring patterns
reference/tools/openapi-tools.md	Generating tools from an OpenAPI 3.0 spec: RestApiTool, auth schemes
reference/tools/tool-authentication.md	Tool auth concepts: API keys, OAuth 2.0, service accounts — load Python sidecar for complete OAuth flow implementation
reference/tools/tool-limitations.md	Tool call limits, unsupported patterns, known constraints
reference/tools/skills-for-agents.md	ADK Skills: reusable packaged tool sets for inter-agent sharing

---

5. Sessions, State & Memory

Persistence and context management across turns and sessions.

Reference	When to Consult
reference/sessions/sessions-overview.md	Sessions architecture: what a session is, lifecycle, service types
reference/sessions/sessions.md	Session CRUD, InMemorySessionService vs DatabaseSessionService, AppConfig
reference/sessions/rewind-sessions.md	Rewinding a session to a prior turn
reference/sessions/migrate-sessions.md	Migrating session data between service backends
reference/sessions/state.md	State concepts: context.state, output_key, state scopes (session/user/app/temp), {key} templating — load language sidecar for code patterns
reference/sessions/memory.md	Long-term memory concepts: MemoryService, search, adding memories — load language sidecar for implementation patterns

---

6. Context

Managing the LLM's context window efficiently.

Reference	When to Consult
reference/context/context-overview.md	What context is in ADK: system prompt, session history, tool results
reference/context/context-caching.md	Caching repeated context (system prompt, documents) to reduce cost/latency
reference/context/context-compression.md	Compressing/summarizing long session history to fit within context limits

---

7. Callbacks

Intercepting and modifying agent behavior at runtime.

Reference	When to Consult
reference/callbacks/callbacks-overview.md	What callbacks are, registration, invocation order
reference/callbacks/types-of-callbacks.md	All 6 callback types: before/after model, before/after tool, before/after agent — load language sidecar for complete runnable examples
reference/callbacks/callback-patterns.md	Design patterns: logging, guardrails, caching, modifying requests/responses

---

8. Components

Core ADK building blocks beyond agents and tools.

Reference	When to Consult
reference/components/artifacts.md	Artifacts: storing/retrieving files and binary blobs within a session
reference/components/events.md	Event system: event types, reading event history, custom events
reference/components/apps.md	App layer: multi-session app management, AppConfig
reference/components/plugins.md	ADK plugins: extending the framework, plugin registration
reference/components/mcp.md	MCP server built into ADK: exposing your agent as an MCP server

---

9. Streaming

Real-time bidirectional communication with agents.

Reference	When to Consult
reference/streaming/streaming-overview.md	Streaming overview: Gemini Live API integration, use cases, architecture
reference/streaming/part1-intro-to-streaming.md	Streaming setup concepts: LiveRequestQueue, run_live() — load Python sidecar for full FastAPI WebSocket example
reference/streaming/part2-sending-messages.md	Sending text and audio messages to a streaming agent
reference/streaming/part3-event-handling.md	Handling streaming events: text chunks, audio, function calls, turn completion
reference/streaming/part4-run-configuration.md	RunConfig for streaming: voice, response modalities, speech config
reference/streaming/part5-audio-images-video.md	Multimodal streaming: audio input/output, images, video frames
reference/streaming/streaming-tools.md	Using tools in streaming mode: streaming-compatible tool patterns
reference/streaming/streaming-configuration.md	Full streaming configuration reference

---

10. A2A Protocol (Agent-to-Agent)

Connecting ADK agents across services and organizations.

Reference	When to Consult
reference/a2a/a2a-introduction.md	A2A protocol overview: agent cards, task lifecycle, discovery
reference/a2a/quickstart-exposing-python.md	Expose a Python ADK agent as an A2A server
reference/a2a/quickstart-consuming-python.md	Consume a remote A2A agent from a Python ADK agent
reference/a2a/quickstart-exposing-go.md	Expose a Go ADK agent as an A2A server
reference/a2a/quickstart-consuming-go.md	Consume a remote A2A agent from a Go ADK agent

---

11. Grounding

Connecting agents to real-world data sources.

Reference	When to Consult
reference/grounding/google-search-grounding.md	Google Search grounding: enable web search in responses, citation handling
reference/grounding/vertex-ai-search-grounding.md	Vertex AI Search grounding: enterprise search over your own documents

---

12. Runtime & CLI

Running, serving, and inspecting agents.

Reference	When to Consult
reference/runtime/runtime-overview.md	Runner, InvocationContext, execution lifecycle overview
reference/runtime/web-interface.md	adk web dev UI: testing agents interactively
reference/runtime/command-line.md	adk run and other CLI commands for running agents
reference/runtime/api-server.md	adk api_server: serving agents as a REST/WebSocket API
reference/runtime/resume-agents.md	Resuming long-running or paused agents
reference/runtime/runtime-config.md	RunConfig: max turns, streaming mode, response modalities
reference/runtime/event-loop.md	Event loop internals: how ADK processes events between runner and agent
reference/reference/cli-reference.md	Full CLI reference: all commands and flags

---

13. Deployment

Taking agents to production.

Reference	When to Consult
reference/deployment/deployment-overview.md	Deployment options comparison: Agent Engine vs Cloud Run vs GKE
reference/deployment/agent-engine.md	Vertex AI Agent Engine: managed serverless deployment
reference/deployment/agent-engine-standard-deployment.md	Standard Agent Engine deployment: packaging, deploying, versioning
reference/deployment/cloud-run.md	Deploying ADK agents to Cloud Run: Dockerfile, service config, scaling
reference/deployment/gke.md	Deploying ADK agents to GKE: Helm charts, autoscaling, GPU support

---

14. Observability & Evaluation

Understanding and measuring agent behavior.

Reference	When to Consult
reference/observability/observability-overview.md	Tracing with OpenTelemetry/Cloud Trace, metrics, Vertex AI evaluation integration
reference/observability/logging.md	Logging configuration: log levels, structured logging, Cloud Logging
reference/evaluation/evaluation-overview.md	Agent evaluation framework: test cases, criteria, running evals
reference/evaluation/evaluation-criteria.md	Evaluation criteria types: trajectory match, response match, custom metrics
reference/evaluation/user-simulation.md	Simulating multi-turn user conversations for automated evaluation

---

15. Safety

Reference	When to Consult
reference/safety.md	Safety guidelines: input/output filtering, responsible AI practices