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Google A2A Blueprints

30

by e-vicius

System prompts and architectural patterns for building scalable AI agents with the Google A2A Protocol and AI SDK.

1 starsUpdated 2026-01-04MIT
Quality Score30/100
Community
7
Freshness
62
Official
30
Skills
10
Protocol
30
🔒 Security
20

Getting Started

1Clone the repository
$ git clone https://github.com/e-vicius/google-a2a-blueprints
2Navigate to the project
$ cd google-a2a-blueprints
3Install dependencies
$ # Check README for install instructions
4Run the agent
$ # Check README for run instructions

README

Google Agent Blueprints

System instructions and architectural rules for building scalable AI Agents with the Google A2A Protocol and Google AI Agent SDK.

Google AI Protocol IDE

📖 About This Repository

Building production-grade AI agents requires more than just good prompts—it requires strict architectural enforcement.

Google Agent Blueprints is a curated collection of System Prompts and IDE Rulesets designed to force your AI coding assistant (Cursor, Windsurf, Antigravity, etc.) to adhere to best practices defined by Google's Agent-to-Agent (A2A) protocol and the Google AI Agent SDK.

Instead of manually reminding your AI to "use a shared database" or "follow the A2A handshake," you can drop these files into your project to enforce those patterns automatically.

🚀 The Tech Stack

This repository focuses specifically on:

  • Google AI Agent SDK: Best practices for scaffolding agents, tool definitions, and standard implementations.
  • Google A2A (Agent-to-Agent) Protocol: Rules for defining how independent agents discover, handshake, and communicate with each other securely.
  • Context Systems: Architectural patterns for shared memory and state management across multi-agent fleets.

📂 Repository Contents

Blueprint Description Use Case
rules/context-systems.md Enforces the "Shared Memory" architecture. Prevents siloed agent state by mandating a central memory microservice. Multi-Agent Fleets
rules/a2a-discovery.md Enforces the "Agent Card" pattern for discovery and interoperability. Multi-Agent Fleets
rules/multi-agent-orchestration.md Enforces the "Coordinator Pattern" for orchestrating multi-agent workflows. Multi-Agent Fleets
rules/agent-tools-and-safety.md Enforces the "Pydantic Mandate" for tool definition and safety. Agent Development
rules/agent-testing-standards.md Enforces the "Golden Dataset" pattern for testing. Agent Development
other/agent-observability.md Enforces the "Correlation ID" mandate for observability. Agent Development

🛠 How to Use

For Cursor / Windsurf / Antigravity

  1. Navigate to the pattern you want to implement (e.g., context-systems.md).
  2. Copy the raw content.
  3. Paste it into your project's .cursorrules or .windsurfrules file (or your specific IDE's system instruction settings).
  4. Result: Your AI assistant now "knows" how to architect systems according to that specific Google protocol and will refuse to generate code that violates it.

For Custom Agents

You can also inject these markdown files directly into your Agent's System Prompt to ensure they understand their own architectural constraints at runtime.

🤝 Contributing

We welcome contributions! If you have optimized a set of rules for the Google Agent ecosystem or found a better way to instruct AI IDEs on A2A patterns, please submit a PR.


Capabilities

StreamingPush NotificationsMulti-TurnAuth: none
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