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OneWave-AI

Agent To Agent skill

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

$npx skills add OneWave-AI/claude-skills --skill agent-to-agent
View this skill on GitHubOneWave-AI/claude-skills/agent-to-agent/SKILL.md
Pack stars
423
Pack installs
72k
Alyn Score
58/99
Updated
22 days ago
License
MIT
– views – installs via Alyn

OneWave-AI

Agent To Agent

Install Agent To Agent

Pick your agent. Every command is ready to paste.

$npx skills add OneWave-AI/claude-skills --skill agent-to-agent

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads agent-to-agent when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the agent-to-agent skill”. In Codex, type $agent-to-agent.

The skill itself

SKILL.md

FolderGitHub

Agent-to-Agent (A2A) Communication Protocol

Act as the A2A Coordinator: a protocol layer that lets multiple Claude Code agents communicate, collaborate, and delegate work through structured message passing, shared context, and formal handoffs. Orchestrate every interaction through the shared context file .a2a-context.json and the Agent tool.

Contents

  • references/protocol.md — message format, message types, lifecycle, shared context schema, atomic read-modify-write, context size management.
  • references/registry.md — agent registration, capability discovery, built-in agent templates.
  • references/patterns.md — request/response, pipeline, fan-out/fan-in, conversation, supervisor.
  • references/handoff.md — structured handoff, acceptance, rejection, chain tracking.
  • references/error-handling.md — timeouts, rejections, deadlock detection, degradation, escalation matrix.
  • references/workflows.md — worked examples (research+writer, code+review, sales+technical).
  • references/operations.md — coordination commands, best practices, monitoring, security, init detail.

Workflow

  1. Understand the goal. Determine what the user wants to accomplish with multiple agents.
  2. Design the team. Decide which agents are needed; draw from the templates in references/registry.md or write custom specs.
  3. Choose the pattern. Select pipeline, fan-out/fan-in, conversation, or supervisor from references/patterns.md. Prefer pipeline when order matters, fan-out when subtasks are independent.
  4. Initialize. Locate the project root. Read .a2a-context.json if it exists and report current state; otherwise create it from the template in references/operations.md. Register every agent into the agents section per references/registry.md.
  5. Execute. Dispatch agents via the Agent tool following the chosen pattern. Structure each agent prompt with identity, context, task, output location, protocol, and constraints (see references/operations.md). For parallelism, issue multiple Agent tool calls in a single response.
  6. Coordinate handoffs. When an agent transfers a task, require a full handoff payload and an ACK, and append to the task chain. Follow references/handoff.md.
  7. Monitor and recover. Read .a2a-context.json to track progress. On timeout, rejection, deadlock, or failure, apply the procedures and escalation matrix in references/error-handling.md. Cap retries at 3 before escalating to the user.
  8. Deliver. Merge all agent findings into the conclusions section and present the final output.

Core Rules

  • Treat .a2a-context.json as the single source of truth. Read it before acting; write the complete file back after modifying. Follow the atomic read-modify-write procedure in references/protocol.md.
  • Conform every inter-agent message to the schema in references/protocol.md.
  • Confine each agent to writing its own section plus shared conclusions. Restrict task assignment changes to the Coordinator.
  • Never write secrets to .a2a-context.json; pass sensitive data in-memory through Agent prompts and add the file to .gitignore.
  • Require explicit ERROR messages for all failures; never fail silently. Run context summarization when the file exceeds 50KB.

Minimal Example: 2-Agent Pipeline

User: "Research the top 5 AI frameworks and write a comparison article."

Coordinator:
1. Create .a2a-context.json
2. Register: researcher, writer
3. Dispatch researcher: "Search for top 5 AI frameworks, compare features, performance, ecosystem"
4. Read researcher's findings from shared context
5. Dispatch writer: "Using the research findings, write a 1200-word comparison article"
6. Read writer's draft from shared context
7. Present the final article to the user

Tips for Agent To Agent

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • It bundles reference files. The agent reads them only when needed, so they cost no context until then.
  • • It is part of a pack with 30 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Agent To Agent

What does the Agent To Agent skill do?

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

How do I install Agent To Agent?

Run "npx skills add OneWave-AI/claude-skills --skill agent-to-agent" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Agent To Agent work in Cursor and Codex?

Yes. Agent To Agent uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Agent To Agent free?

Agent To Agent is open source on GitHub under the MIT license. It is free to install; check the license before commercial use.

Who made Agent To Agent?

Agent To Agent is published by OneWave-AI in the OneWave-AI/claude-skills repository, together with 29 other skills.

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