How to Get Your ADK Agent into Google's Official Community Showcase
How to Get Your ADK Agent into Google’s Official Community Showcase
Last week, Bob’s Brain became one of only 4 projects in Google’s official Agent Starter Pack community showcase. Here’s the tactical playbook for how we got there—and what it means for your ADK projects.
The Numbers That Matter
| Metric | Value |
|---|---|
| Repository Stars | 3,690 |
| Total Forks | 1,041 |
| External Contributors | 1 (us) |
| Community Showcase Projects | 4 |
Out of 1,041 forks, we’re the only external contributor. That’s a 0.1% conversion rate from “forked the repo” to “actually contributed back.”
What We Submitted
PR #580 added Bob’s Brain to the community showcase with:
- Production deployment on Vertex AI Agent Engine
- Multi-agent architecture (10 agents: orchestrator → foreman → 8 specialists)
- Hard Mode compliance (R1-R8 architectural rules enforced via CI)
- 95/100 quality score with 65%+ test coverage
- 145 documentation files including 28 canonical standards
The Review Process
- Automated CLA check - Sign Google’s Contributor License Agreement
- Gemini Code Assist review - Automated code analysis and suggestions
- Maintainer review - Human approval from Google team
Total time from PR submission to merge: ~36 hours
Google maintainer’s response: “thanks for this, approved and merged!”
Why This Matters for Your ADK Projects
Being in Google’s showcase provides:
- Third-party validation - Google’s team reviewed and approved your architecture
- Discoverability - 3,690+ developers see your reference implementation
- Credibility - “Google-recognized” carries weight in other contributions
We immediately leveraged this in our other open PRs:
- A2A Samples PR #419 (foreman-worker pattern demo)
- Linux Foundation AI Card PR #7 (reference implementation)
Both now include a “Google Recognition” section citing the merged PR.
The Technical Bar
What gets accepted into the showcase:
| Requirement | Our Implementation |
|---|---|
| Production-ready | Deployed on Vertex AI Agent Engine |
| Well-documented | 145 docs, 28 canonical standards |
| ADK patterns | Hard Mode R1-R8 compliance |
| Real-world use case | Multi-agent SWE department |
What doesn’t matter:
- Repo stars (we had ~50)
- Team size (solo developer)
- Company backing (independent)
Tactical Recommendations
- Focus on documentation - Google values comprehensive docs over clever code
- Show production deployment - Demos are nice; production deployments convince
- Follow ADK patterns strictly - Hard Mode compliance signals seriousness
- Be the first - Empty showcases need content; yours could be featured
Repository Links
- Bob’s Brain: github.com/jeremylongshore/bobs-brain
- Merged PR #580: GoogleCloudPlatform/agent-starter-pack/pull/580
- Community Showcase: agent-starter-pack docs
What’s Next
With Google recognition secured, we’re pursuing:
- A2A Protocol samples (PR #419 pending)
- Linux Foundation AI Card standard (PR #7 pending)
- Conference speaking opportunities
The community contribution strategy is working. Build something real, document it thoroughly, contribute upstream. Recognition follows.
Building production ADK agents? Intent Solutions helps teams deploy multi-agent systems on Vertex AI Agent Engine.