agents-cli-claude
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 a Claude Agent SDK agent scaffolded by agents-cli, so ADK-specific instructions do not apply.
- License 许可
- Apache-2.0
- 最近更新
- 2026-11-05
- Stars
- ★ 6.3k
- Forks
- 734
01 前言 Front Matter
- name
- agents-cli-claude
- description
- 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 a Claude Agent SDK agent scaffolded by agents-cli, so ADK-specific instructions do not apply.
02 资源文件 3
- 参考文档references/claude.md18.7 KB
- 参考文档references/migrate-claude-agent.md20.9 KB
- 参考文档references/migrate-from-aws.md7.8 KB
03 SKILL.md 正文
Claude Agent SDK project (agents-cli)
The agent is a ClaudeAgentOptions exported as root_agent from
app/agent.py. There is no google.adk dependency and no ADK runner. Other
google-agents-cli-* skills assume ADK; where they describe the agent itself,
this skill wins.
Experimental. Deploy to agent_runtime (limits: references/claude.md) or cloud_run.
The model runs on Claude on Gemini platform and must be enabled in Model Garden.
What ADK guidance maps to here
| ADK guidance | This project |
|---|---|
LlmAgent, Agent |
ClaudeAgentOptions(model=..., system_prompt=..., ...) assigned to root_agent |
Agent(name=...) |
AGENT_NAME in app/app_utils/settings.py (ClaudeAgentOptions has no name); keep it equal to create_params.root_agent_name in agents-cli-manifest.yaml |
google.adk.tools, FunctionTool |
@tool(...) async functions, served by create_sdk_mcp_server and passed in mcp_servers |
adk web, agents-cli playground |
Unavailable (no SDK dev UI). Use agents-cli run, or uv run uvicorn app.fast_api_app:app --port 8080 |
ADK runner behind agents-cli run |
agents-cli run runs root_agent in process |
agents-cli eval dataset synthesize, eval optimize |
Unavailable: both drive the agent through ADK. The command says so and exits |
agents-cli eval generate --url (traces from a served agent) |
Unavailable: the server speaks A2A, not ADK's /run_sse. eval generate runs root_agent in process; the command refuses --url |
| ADK sessions | Claude sessions, one per A2A conversation; scaffold with --session-type cloud_sql to keep them across instances |
The contract
app/agent.pyexportsroot_agent: ClaudeAgentOptions. Only it changes when you change the agent.app/app_utils/claude.pyruns it. Leaveapp/app_utils/alone.- The served agent's own
CLAUDE.md,.claude/and.mcp.jsongo inagent_config/. app/fast_api_app.pyexposesapp. Every deployment target runsuvicorn app.fast_api_app:app.
Adding a tool
@tool("lookup_order", "Look up an order by id.", {"order_id": str})
async def lookup_order(args: dict[str, Any]) -> dict[str, Any]:
return {"content": [{"type": "text", "text": f"Order {args['order_id']}: shipped"}]}
server = create_sdk_mcp_server(name="orders", tools=[lookup_order])
root_agent = ClaudeAgentOptions(
...,
mcp_servers={"orders": server},
tools=[], # no built-in Claude Code tools
allowed_tools=["mcp__orders__lookup_order"], # mcp__<server>__<tool>
)
A tool missing from allowed_tools is not available to the agent. Subagents (agents=
or agent_config/.claude/agents/) run through the built-in Agent tool: add "Agent" to both
tools and allowed_tools. Built-in tools
(WebFetch, WebSearch, Read, Bash, ...) go in both tools and allowed_tools;
keep Bash and file-editing tools out of a served agent unless the user asks.
Commands
agents-cli install # uv sync
agents-cli run "hello" # run root_agent in process; prints a session id
agents-cli run "and?" --session-id <id> # continue that conversation
agents-cli eval generate --dataset tests/eval/datasets/basic-dataset.json -o tests/eval/output/
agents-cli eval grade --traces tests/eval/output/<dataset>.json --config tests/eval/eval_config.yaml
agents-cli deploy
agents-cli scaffold enhance -d cloud_run --cicd-runner github_actions # add infra later
run, eval generate, publish gemini, playground, eval dataset and
eval optimize are overridden by agents-cli-extension.yaml at the project root.
Prefix any command with AGENTS_CLI_DISABLE_OVERRIDES=1 to reach the built-in instead.
Serving
A2A: JSON-RPC at POST /a2a/app, card at /a2a/app/.well-known/agent-card.json,
health at /health; over A2A, text streams as it is generated. On Agent Runtime, also
:query and :streamQuery (new sessions and turns), which agents-cli run --mode adk
and an ingress Agent Gateway use. See references/claude.md for sessions, telemetry
and deployment.
Common mistakes
- Renaming
root_agentorapp, which breaksrun, eval and deploy. - Leaving
toolsunset: the agent then gets every built-in Claude Code tool. - Using a model id that is not enabled on Gemini platform for the project.
- Reaching for
eval dataset synthesizeoreval optimize: they need ADK. Write cases intotests/eval/datasets/and useeval generate+eval grade. - Expecting
/run_sseor ADK's REST session routes; this server serves A2A and Agent Runtime's:query/:streamQuery.
References
references/claude.md— how a turn runs, model access, project settings, sessions, calling other agents, telemetry and logs.references/migrate-claude-agent.md— moving an existing Claude Agent SDK agent into this project and onto GCP.references/migrate-from-aws.md— extra migration steps for an agent running on AWS.
04 同仓库更多 Skills
google-agents-cli-workflow
This skill should be used when the user wants to "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle and coding guidelines. Entrypoint for building ADK agents. Always active — provides the full workflow (scaffold, build, evaluate, deploy, publish, observe), code preservation rules, model selection guidance, and troubleshooting steps for ADK or any agent development.
google-agents-cli-scaffold
This skill should be used when the user wants to "create an agent project", "start a new ADK project", "build me a new agent", "add CI/CD to my project", "add deployment", "enhance my project", or "upgrade my project". Part of the agents-cli skills suite. Covers `agents-cli scaffold create`, `scaffold enhance`, and `scaffold upgrade` commands, template options, deployment targets, and the prototype-first workflow. Do NOT use for writing agent code (ADK projects: use google-agents-cli-adk-code) or deployment operations (use google-agents-cli-deploy).
google-agents-cli-publish
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
google-agents-cli-observability
This skill should be used when the user wants to "set up tracing", "monitor my agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed agents, including ADK (Agent Development Kit) agents. Covers Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations (AgentOps, Phoenix, MLflow, etc.), and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment setup (use google-agents-cli-deploy) or API code patterns (use google-agents-cli-adk-code).
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).
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).