adk-engineer
Execute software engineer specializing in creating production-ready ADK agents with best practices, code structure, testing, and deployment automation. Use when asked to "build ADK agent", "create agent code", or "engineer ADK application". Trigger with relevant phrases based on skill purpose.
Best use case
adk-engineer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Execute software engineer specializing in creating production-ready ADK agents with best practices, code structure, testing, and deployment automation. Use when asked to "build ADK agent", "create agent code", or "engineer ADK application". Trigger with relevant phrases based on skill purpose.
Teams using adk-engineer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/adk-engineer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How adk-engineer Compares
| Feature / Agent | adk-engineer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Execute software engineer specializing in creating production-ready ADK agents with best practices, code structure, testing, and deployment automation. Use when asked to "build ADK agent", "create agent code", or "engineer ADK application". Trigger with relevant phrases based on skill purpose.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# ADK Engineer
Engineer production-ready Agent Development Kit (ADK) agents and multi-agent systems: clean structure, testability, safe tool usage, and deployment automation.
## Overview
Use this skill to design and implement ADK agent code that is maintainable and shippable: clear module boundaries, structured tool interfaces, regression tests, and a deployment checklist (local or Agent Engine).
## Prerequisites
- A target runtime (Python/Java/Go) consistent with the project’s pinned versions
- ADK installed (and any required model/provider SDKs configured)
- A test runner available in the repo (unit tests at minimum)
- If deploying: access to a Google Cloud project and permissions for the chosen deployment target
## Instructions
1. Clarify requirements: agent goals, tool surface, latency/cost constraints, and deployment target.
2. Propose architecture: single agent vs multi-agent, orchestration pattern, state strategy (Memory Bank / external store).
3. Scaffold structure: agent entrypoint(s), tool modules, config, and tests.
4. Implement incrementally:
- add one tool at a time with input validation and structured outputs
- add regression tests for each tool and critical prompt flows
5. Add operational guardrails: retries/backoff, timeouts, logging, and safe error messages.
6. Validate locally (tests + smoke prompts) and provide a deployment plan (when requested).
## Output
- A concrete architecture plan and file layout
- Agent and tool implementations (or patches) with tests
- A validation checklist (commands to run, expected outputs, and failure triage)
- Optional: deployment instructions and post-deploy health checks
## Error Handling
- Build/test failures: isolate the failing module, minimize the repro, fix, and add a regression test.
- Tool/runtime errors: enforce structured error responses and safe retries where appropriate.
- Deployment failures: provide the exact failing command, logs to inspect, and least-privilege IAM fixes.
## Examples
**Example: Productionizing an existing ADK agent**
- Request: “Refactor this agent into a clean module structure and add tests before we deploy.”
- Result: reorganized `src/` layout, tool boundaries, a test suite, and a deployment checklist.
**Example: Multi-agent workflow**
- Request: “Build a validator + deployer + monitor agent team with a sequential orchestrator.”
- Result: orchestrator skeleton, per-agent responsibilities, and smoke tests for each step.
## Resources
- Full detailed playbook (kept for reference): `${CLAUDE_SKILL_DIR}/references/SKILL.full.md`
- Repo standards (source of truth):
- `000-docs/6767-a-SPEC-DR-STND-claude-code-plugins-standard.md`
- `000-docs/6767-b-SPEC-DR-STND-claude-skills-standard.md`
- ADK / Agent Engine docs: https://cloud.google.com/vertex-ai/docs/agent-engineRelated Skills
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