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
Confirm scope: local-only agent scaffold vs Vertex AI Agent Engine deployment.
Choose an architecture:
Single agent (ReAct) for adaptive tool-driven tasks
Multi-agent system (specialists + orchestrator) for complex, multi-step workflows
Define the tool surface (built-in ADK tools + any custom tools you need) and required credentials.
Scaffold the project:
src/agents/, src/tools/, tests/, and a dependency file (pyproject.toml or requirements.txt)
Implement the minimum viable agent and a smoke test prompt; add regression tests for tool failures.
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
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1---2name: helixdevelopment-helixagent-adk-agent-builder3description: ADK Agent Builder4---5# ADK Agent Builder67Build production-ready agents with Google’s Agent Development Kit (ADK): scaffolding, tool wiring, orchestration patterns, testing, and optional deployment to Vertex AI Agent Engine.89## Overview1011- Creates a minimal, production-oriented ADK scaffold (agent entrypoint, tool registry, config, and tests).12- Supports single-agent ReAct-style workflows and multi-agent orchestration (Sequential/Parallel/Loop).13- Produces a validation checklist suitable for CI (lint/tests/smoke prompts) and optional Agent Engine deployment verification.1415## Prerequisites1617- Python runtime compatible with your project (often Python 3.10+)18- `google-adk` installed and importable19- If deploying: access to a Google Cloud project with Vertex AI enabled and permissions to deploy Agent Engine runtimes20- Secrets available via environment variables or a secret manager (never hardcoded)2122## Instructions23241. Confirm scope: local-only agent scaffold vs Vertex AI Agent Engine deployment.252. Choose an architecture:26 - Single agent (ReAct) for adaptive tool-driven tasks27 - Multi-agent system (specialists + orchestrator) for complex, multi-step workflows283. Define the tool surface (built-in ADK tools + any custom tools you need) and required credentials.294. Scaffold the project:30 - `src/agents/`, `src/tools/`, `tests/`, and a dependency file (`pyproject.toml` or `requirements.txt`)315. Implement the minimum viable agent and a smoke test prompt; add regression tests for tool failures.326. If deploying, produce an `adk deploy ...` command and a post-deploy validation checklist (AgentCard/task endpoints, permissions, logs).3334## Output3536- A repo-ready ADK scaffold (files and directories) plus starter agent code37- Tool stubs and wiring points (where to add new tools safely)38- A test + validation plan (unit tests and a minimal smoke prompt)39- Optional: deployment commands and verification steps for Agent Engine4041## Error Handling4243- Dependency/runtime issues: provide pinned install commands and validate imports.44- Auth/permission failures: identify the missing role/API and propose least-privilege fixes.45- Tool failures/rate limits: add retries/backoff guidance and a regression test to prevent recurrence.4647## Examples4849**Example: Scaffold a single ReAct agent**50- Request: “Create an ADK agent that summarizes PRs and proposes test updates.”51- Result: agent entrypoint + tool registry + a smoke test command for local verification.5253**Example: Multi-agent orchestrator**54- Request: “Build a supervisor + deployer + verifier team and deploy to Agent Engine.”55- Result: orchestrator skeleton, per-agent responsibilities, and `adk deploy ...` + post-deploy health checks.5657## Resources5859- Full detailed guide (kept for reference): `{baseDir}/references/SKILL.full.md`60- Repo standards (source of truth):61 - `000-docs/6767-a-SPEC-DR-STND-claude-code-plugins-standard.md`62 - `000-docs/6767-b-SPEC-DR-STND-claude-skills-standard.md`63- ADK / Agent Engine docs: https://cloud.google.com/vertex-ai/docs/agent-engine6465---66> Converted and distributed by [TomeVault](https://tomevault.io/claim/helixdevelopment) — claim your Tome and manage your conversions.67<!-- tomevault:4.0:skill_md:2026-04-13 -->
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