How do I ensure my executor is protocol-compliant?

The skill includes dedicated validation and testing scripts (validate-executor.sh and test-executor.sh) to check your implementation against the official A2A specification.

Can I handle long-running tasks with these patterns?

Absolutely. The skill includes specific patterns for asynchronous executors that return task IDs immediately, manage internal state, and provide status updates or callbacks upon completion.

Does this skill support Python development?

Yes, it provides production-ready templates and examples for both TypeScript (Node.js 18+) and Python (3.9+).

What kind of retry strategies are supported?

It provides implementation patterns for several strategies, including exponential backoff, linear backoff, and fixed delay, specifically designed to handle transient network or resource errors.

What is an A2A executor?

An A2A executor is a specialized component that implements the Agent-to-Agent protocol to receive, validate, and process tasks sent from one AI agent to another, facilitating complex multi-agent workflows.

A2A Executor Patterns

Name: A2A Executor Patterns
Author: vanman2024

byvanman2024

データサイエンスとML

Implements standardized Agent-to-Agent (A2A) protocol executors with production-ready patterns for task management and agent coordination.

概要

This skill provides a comprehensive library of implementation patterns for building robust Agent-to-Agent (A2A) protocol executors. It offers a structured approach to creating task handlers using various execution modes—including synchronous, asynchronous, streaming, and batch processing—in both TypeScript and Python. By incorporating built-in patterns for validation, error recovery with exponential backoff, and middleware for logging and metrics, it ensures that agent-to-agent communications are reliable, scalable, and compliant with the A2A protocol specification.

主な機能

Comprehensive task state management for tracking long-running lifecycles
Built-in middleware components for logging, metrics, and rate limiting
Validation scripts to ensure compliance with the A2A protocol specification
Multi-language templates (TypeScript and Python) for sync, async, and streaming executors
Configurable error handling and exponential backoff retry logic
0 GitHub stars

ユースケース

Creating long-running LLM inference workflows with status updates and streaming results
Implementing resilient agent communication layers with automatic retries and error recovery
Building a backend service that processes complex tasks requested by autonomous AI agents

概要

主な機能

Comprehensive task state management for tracking long-running lifecycles
Built-in middleware components for logging, metrics, and rate limiting
Validation scripts to ensure compliance with the A2A protocol specification
Multi-language templates (TypeScript and Python) for sync, async, and streaming executors
Configurable error handling and exponential backoff retry logic
0 GitHub stars

ユースケース

Creating long-running LLM inference workflows with status updates and streaming results
Implementing resilient agent communication layers with automatic retries and error recovery
Building a backend service that processes complex tasks requested by autonomous AI agents