adk-agent-builder

# ADK Agent Builder Build production-ready agents with Google’s Agent Development Kit (ADK): scaffolding, tool wiring, orchestration patterns, testing, and optional deployment to Vertex AI Agent Engine. ## Overview - Creates a minimal, production-oriented ADK scaffold (agent entrypoint, tool registry, config, and tests). - Supports single-agent ReAct-style workflows and multi-agent orchestration (Sequential/Parallel/Loop). - Produces a validation checklist suitable for CI (lint/tests/smoke prompts) and optional Agent Engine deployment verification. ## Prerequisites - Python runtime compatible with your project (often Python 3.10+) - `google-adk` installed and importable - If deploying: access to a Google Cloud project with Vertex AI enabled and permissions to deploy Agent Engine runtimes - Secrets available via environment variables or a secret manager (never hardcoded) ## Instructions 1. Confirm scope: local-only agent scaffold vs Vertex AI Agent Engine deployment. 2. Choose an architecture: - Single agent (ReAct) for adaptive tool-driven tasks - Multi-agent system (specialists + orchestrator) for complex, multi-step workflows 3. Define the tool surface (built-in ADK tools + any custom tools you need) and required credentials. 4. Scaffold the project: - `src/agents/`, `src/tools/`, `tests/`, and a dependency file (`pyproject.toml` or `requirements.txt`) 5. Implement the minimum viable agent and a smoke test prompt; add regression tests for tool failures. 6. If deploying, produce an `adk deploy ...` command and a post-deploy validation checklist (AgentCard/task endpoints, permissions, logs). ## Output - A repo-ready ADK scaffold (files and directories) plus starter agent code - Tool stubs and wiring points (where to add new tools safely) - A test + validation plan (unit tests and a minimal smoke prompt) - Optional: deployment commands and verification steps for Agent Engine ## Error Handling - Dependency/runtime issues: provide pinned install commands and validate imports. - Auth/permission failures: identify the missing role/API and propose least-privilege fixes. - Tool failures/rate limits: add retries/backoff guidance and a regression test to prevent recurrence. ## Examples **Example: Scaffold a single ReAct agent** - Request: “Create an ADK agent that summarizes PRs and proposes test updates.” - Result: agent entrypoint + tool registry + a smoke test command for local verification. **Example: Multi-agent orchestrator** - Request: “Build a supervisor + deployer + verifier team and deploy to Agent Engine.” - Result: orchestrator skeleton, per-agent responsibilities, and `adk deploy ...` + post-deploy health checks. ## Resources - Full detailed guide (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