adk-engineer

# 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): `{baseDir}/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-engine