google-agents-cli-adk-code

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" — in a project that needs ADK (Agent Development Kit) API patterns and code examples. It provides a quick reference for agent types, tool definitions, orchestration patterns, callbacks, state management, the graph Workflow API, and reference recipes to study. Do NOT use for scaffolding (use google-agents-cli-scaffold) or deployment (use google-agents-cli-deploy).

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저장소: google/agents-cli
최근 소스 활동: 2026년 10월 12일 19:37
감지된 SKILL.md 언어: 영어
스타: 6,094
포크: 700

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npx skills add https://github.com/google/agents-cli --skill google-agents-cli-adk-code

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SKILL.md

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name: google-agents-cli-adk-code
description: 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" — in a project that needs ADK (Agent Development Kit) API patterns and code examples. It provides a quick reference for agent types, tool definitions, orchestration patterns, callbacks, state management, the graph Workflow API, and reference recipes to study. Do NOT use for scaffolding (use google-agents-cli-scaffold) or deployment (use google-agents-cli-deploy).
metadata: {"author":"Google","license":"Apache-2.0","version":"1.10.0","requires":{"bins":["agents-cli"],"install":"uv tool install google-agents-cli"}}

# ADK Code Reference Activate `/google-agents-cli-workflow` first for required development phases and scaffolding steps. ## 1. Study Recipes (No Project Needed) **Python — read the topic index in `references/samples.md` before answering "how do I build X".** Worked implementations exist for: sandboxed/per-user code execution, agent-loadable `SKILL.md` skills, cross-session memory, approval gates before risky actions, tool guardrails, per-user credentials, and scheduled/event-driven runs. **Go — read the upstream [`examples/`](https://github.com/google/adk-go/tree/main/examples).** clone the repo and read the one matching the capability you need before implementing it. ## 2. Prerequisites for Writing Code Do NOT write agent code until a project is scaffolded. 1. Verify project: run `agents-cli info` (proceed if config exists). 2. New project: run `agents-cli scaffold create <name>` — add `--agent adk_go` for Go. 3. Existing code: run `agents-cli scaffold enhance .`. ## Quick Reference — Most Common Patterns See `references/adk-python.md` and `references/adk-go.md` for Python and Go code examples, respectively. --- ## References Use the cheatsheets for common patterns. For deep knowledge, fetch the docs index or inspect the installed package. | Reference | Language | When to read | |------|------|-------------| | `references/samples.md` | Python | **Topic-indexed catalog of ADK reference recipes.** Read in workflow Phase 1 — before scaffolding and before writing code — maps a capability to the recipe that implements it. | | `references/adk-python.md` | Python | Core ADK API: `Agent`, tools, callbacks, plugins, state, artifacts, multi-agent systems, `SequentialAgent` / `ParallelAgent` / `LoopAgent`, custom `BaseAgent`, `ManagedAgent` (server-hosted first-party agents), A2A protocol, A2UI. Default for most agents. | | `references/adk-python-workflows.md` | Python | Graph-based Workflow API (ADK Python 2.0): nodes, edges, fan-out/fan-in, HITL, parallel processing. Use when you need explicit graph topology. | | `references/adk-python-live.md` | Python | Live and voice agents: `Runner.run_live`, `LiveRequestQueue`, model and regional availability, voice/`speech_config`, VAD, session limits, `/run_live` serving. Use for real-time voice or video agents. | | `references/adk-go.md` | Go | Core ADK Go API: `llmagent`, tools, callbacks, plugins, state, artifacts, multi-agent systems, sequential/parallel/loop agents, custom agents, the runner, serving over HTTP, A2A protocol, and ambient triggers. Default for most agents. | | `references/adk-go-workflows.md` | Go | Graph-based Workflow API: nodes, edges, fan-out/fan-in, HITL, parallel processing. Use when you need explicit graph topology. | | [`examples/`](https://github.com/google/adk-go/tree/main/examples) | Go | Runnable upstream programs — the closest thing to a recipe catalog for Go. | | `curl https://adk.dev/llms.txt` | Python | Docs index (every page title + URL). Fetch it, then `WebFetch` the specific page for anything beyond the cheatsheets. | | Installed ADK package | Python | Exact signatures and symbols — inspect the source (see "Inspecting ADK Source Code" in `references/adk-python.md`). | ## Related Skills - `/google-agents-cli-workflow` — Development workflow, coding guidelines, and operational rules - `/google-agents-cli-scaffold` — Project creation and enhancement with `agents-cli scaffold create` / `scaffold enhance` - `/google-agents-cli-eval` — Evaluation methodology, dataset schema, and the eval-fix loop - `/google-agents-cli-deploy` — Deployment targets, CI/CD pipelines, and production workflows

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agents-cli-langchain

Use when working in this project — adding tools, editing the agent, running, evaluating, serving or deploying it — or when guidance mentions ADK, LlmAgent, google.adk, adk web, or an ADK runner. This project is LangChain/LangGraph scaffolded by agents-cli, so ADK-specific instructions do not apply.

2026-10-12

google-agents-cli-deploy

This skill should be used when the user wants to "deploy an agent", "deploy my ADK agent", "set up CI/CD", "configure secrets", "troubleshoot a deployment", or needs guidance on Agent Runtime, Cloud Run, or GKE deployment targets, or binding an agent to an Agent Gateway. Covers deployment workflows, service accounts, rollback, and production infrastructure. Applies to any framework agents-cli deploys (ADK, LangChain, ...). Part of the agents-cli skills suite. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), evaluation (use google-agents-cli-eval), or project scaffolding (use google-agents-cli-scaffold).

2026-10-12

google-agents-cli-eval

This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

2026-10-12

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google-agents-cli-adk-code

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