google-adk-agents
Build, evaluate, and deploy agents with Google's Agent Development Kit (ADK).
Skill by Biomedical OS Team
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/mdbabumiamssm-google-adk-agents
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: devops, productivity, agent-building
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/google-adk-agents
What's inside
- Skill name
google-adk-agents- Description
- Build, evaluate, and deploy agents with Google's Agent Development Kit (ADK). Use when you want code-first multi-agent systems, workflow agents, MCP tools, or Google-supported agent deployment paths.
- License
- MIT
- Metadata
- author: Biomedical OS Team · version: 2026.04 · upstream_repo: https://github.com/google/adk-python
- Instructions
- 26 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- name: "google-adk-agents" does not match folder "Google_ADK_Agents"
- allowed-tools: must be a space-separated string
Files (3)
- SKILL.md
- openai.yaml · agents/
- sources.md · references/
SKILL.md (first lines)
# Google ADK Agents Use this skill when you want Google's agent framework primitives instead of retrofitting agent behavior onto a generic app framework. ## Workflow 1. Pick the runtime language first: Python is the default, but ADK also supports TypeScript, Go, and Java. 2. Decide whether the problem is best modeled as an LLM agent, a workflow agent, or a multi-agent system. 3. Choose the tool surface: function tools, MCP tools, OpenAPI tools, or native integrations. 4. Define evaluation and runtime strategy before deployment, not after. 5. Validate locally, then promote to managed runtime or production infra only after passing a small eval set. ## Guardrails - Keep agent boundaries explicit; avoid one giant catch-all agent. - Prefer documented ADK primitives over undocumented framework internals. - Record the model/provider abstraction used so the workflow stays reproducible. - Treat third-party integrations as optional until auth, quotas, and failure modes are documented. ## Output Requirements - State the ADK runtime and language. - State the agent topology (single, workflow, or multi-agent). - State the evaluation plan and one production risk.
From mdbabumiamssm/LLMs-Universal-Life-Science-and-Clinical-Skills-, MIT.
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Signals
- Stars
- 36
- Forks
- 8
- Open issues
- 0
- Last commit (this folder)
- Apr 14, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 2026.04
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
google-adk-agents skill. Agent Mart. https://agentmart.dev/skills/mdbabumiamssm-google-adk-agents (last updated 2026-10-24)