Agent skill

agenticx-a2a-connector

Guide for using the A2A (Agent-to-Agent) communication protocol in AgenticX including agent discovery, skill invocation, remote agent cards, and distributed agent systems. Use when the user wants agents to communicate with each other, set up distributed agent systems, invoke remote agent skills, or build agent-to-agent workflows.

Stars 106
Forks 12

Install this agent skill to your Project

npx add-skill https://github.com/DemonDamon/AgenticX/tree/main/agenticx/skills/agenticx-a2a-connector

Metadata

Additional technical details for this skill

author
AgenticX
version
0.3.6

SKILL.md

AgenticX A2A Connector

Guide for building distributed, inter-communicating agent systems using the A2A protocol.

What is A2A?

A2A (Agent-to-Agent) is a protocol that enables agents to discover each other's capabilities and invoke them as if they were local tools. This allows building distributed agent systems where specialized agents collaborate across network boundaries.

Core Components

Component Purpose
AgentCard Advertises an agent's identity and skills
Skill Describes a capability an agent offers
A2ASkillTool Wraps a remote skill as a local tool
A2ASkillToolFactory Batch-creates tools from an AgentCard
A2AClient HTTP client for calling remote agents

Agent Cards

An AgentCard declares what an agent can do:

python
from agenticx.protocols import AgentCard, Skill

card = AgentCard(
    name="Research Agent",
    description="Specializes in web research and report generation",
    url="http://research-agent:8000",
    skills=[
        Skill(
            name="web_research",
            description="Search the web and compile findings",
            parameters_schema={
                "type": "object",
                "properties": {
                    "query": {"type": "string"},
                    "depth": {"type": "integer", "default": 3}
                },
                "required": ["query"]
            }
        ),
        Skill(
            name="generate_report",
            description="Generate a structured report from research data",
            parameters_schema={
                "type": "object",
                "properties": {
                    "topic": {"type": "string"},
                    "format": {"type": "string", "enum": ["markdown", "html"]}
                },
                "required": ["topic"]
            }
        )
    ]
)

Using Remote Agent Skills as Tools

Single Skill

python
from agenticx.protocols import A2ASkillTool

tool = A2ASkillTool(
    agent_url="http://research-agent:8000",
    skill_name="web_research"
)

# Use like any local tool
result = tool.run(query="latest AI trends", depth=5)

All Skills from an Agent

python
from agenticx.protocols import A2ASkillToolFactory

factory = A2ASkillToolFactory()
tools = factory.create_tools(agent_card=card)

# tools is a list of A2ASkillTool instances, one per skill
for t in tools:
    print(f"Tool: {t.name} — {t.description}")

A2A Client

Low-level client for direct communication:

python
from agenticx.protocols import A2AClient

client = A2AClient(base_url="http://research-agent:8000")

# Discover capabilities
card = client.get_agent_card()

# Invoke a skill
result = client.invoke_skill(
    skill_name="web_research",
    parameters={"query": "quantum computing", "depth": 3}
)

Building an A2A-Enabled Agent

Expose your agent as an A2A service:

python
from agenticx import Agent
from agenticx.protocols import A2AServer

agent = Agent(
    id="specialist",
    name="Data Specialist",
    role="Data Analysis",
    goal="Analyze datasets",
    organization_id="team-a"
)

server = A2AServer(agent=agent, port=8001)
server.register_skill(
    name="analyze_data",
    handler=my_analysis_function,
    description="Analyze a dataset and return insights"
)
server.start()

Multi-Agent Architecture Pattern

┌─────────────────┐     A2A      ┌──────────────────┐
│  Orchestrator    │────────────→│  Research Agent   │
│  Agent           │             │  (port 8001)      │
│  (port 8000)     │             └──────────────────┘
│                  │     A2A      ┌──────────────────┐
│                  │────────────→│  Analysis Agent   │
│                  │             │  (port 8002)      │
└─────────────────┘             └──────────────────┘

The Orchestrator discovers remote agents via their AgentCards and invokes their skills as tools within its own workflow.

CLI for A2A

bash
# Start an agent as an A2A service
agx serve --port 8001

# The serve command exposes:
# - GET  /.well-known/agent-card  → AgentCard JSON
# - POST /tasks/submit            → Invoke skills

Best Practices

  1. Version your skills — include version in AgentCard metadata
  2. Schema validation — always define parameters_schema for skills
  3. Timeout handling — set reasonable timeouts for remote calls
  4. Retry logic — implement retries for network failures
  5. Health checks — use /health endpoints before routing traffic
  6. Security — authenticate A2A calls in production environments

Expand your agent's capabilities with these related and highly-rated skills.

DemonDamon/AgenticX

agenticx-skill-manager

Guide for managing AgenticX skills including listing, searching, installing, uninstalling, publishing, and running a skill registry server. Use when the user wants to manage skills, find available skills, publish custom skills, set up a skill registry, or understand the skill ecosystem.

106 12
Explore
DemonDamon/AgenticX

agenticx-deployer

Guide for deploying AgenticX agents to production including Docker containerization, Kubernetes orchestration, Volcengine AgentKit cloud deployment, and API server setup. Use when the user wants to deploy agents, containerize applications, set up Kubernetes, configure cloud deployment, or run the AgenticX API server in production.

106 12
Explore
DemonDamon/AgenticX

agenticx-quickstart

AgenticX zero-to-hero quickstart guide. Use when the user wants to get started with AgenticX, create their first project, build their first agent, or run their first workflow. Covers installation, project scaffolding, agent creation, task execution, and CLI basics.

106 12
Explore
DemonDamon/AgenticX

agenticx-workflow-designer

Guide for designing and running AgenticX workflows including sequential pipelines, parallel execution, graph-based orchestration, conditional routing, and trigger services. Use when the user wants to create workflows, orchestrate multiple agents, design agent pipelines, or set up complex multi-step processes.

106 12
Explore
DemonDamon/AgenticX

agenticx-memory-architect

Guide for setting up and using the AgenticX memory system including Mem0 integration, long-term memory, context management, and memory-enhanced agents. Use when the user wants to add memory to agents, persist conversation history, build memory-aware workflows, or integrate with Mem0 for long-term recall.

106 12
Explore
DemonDamon/AgenticX

agenticx-automation-crontask

Build and maintain Machi Desktop scheduled (cron) tasks — default workspace ~/.agenticx/crontask, schedule_task tool, execution contract, and user-facing output. Use when the user wants recurring automation, crontab-style jobs, or to author/fix automation task prompts.

106 12
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results