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agent-to-agent

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.

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Precio sin confirmar★ 287 Estrellas de GitHubRegistro actualizado · 6 sept 2026agent-skill

Resumen

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Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

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.

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

Understand the goal. Determine what the user wants to accomplish with multiple agents.
Design the team. Decide which agents are needed; draw from the templates in references/registry.md or write custom specs.
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.
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.
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.
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.
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.
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

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Metadatos del archivo

name: agent-to-agent
description: 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.
tools: Read, Write, Agent, Bash, Glob, Grep
model: inherit

Ver texto original

---
name: agent-to-agent
description: 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.
tools: Read, Write, Agent, Bash, Glob, Grep
model: inherit
---

# Agent-to-Agent (A2A) Communication Protocol

## 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
```

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Licencia: MIT
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Licencia: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
The SKILL.md references external files (references/*.md) that are not fully included in the excerpt, but the repository appears to contain them. This is acceptable as long as the full skill is distributed with those files.
The shared context file .a2a-context.json is a single point of failure; while atomic read-modify-write is specified, concurrent agents could still race if not strictly serialized. The protocol relies on the coordinator to enforce ordering, which is a design assumption.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 287 stars, 43 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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Fuente y notas de uso

Indexado

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Repositorio fuente: OneWave-AI/claude-skills
Licencia: MIT
Versión: 1.0.0
Último push de GitHub: 11 ago 2026
Registro actualizado: 6 sept 2026
Ruta de instrucciones: agent-to-agent/SKILL.md @ 82859c0ebaff

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

68/100

Prometedor

Confianza

57/100

Do not auto-install

Auditoría

73/100

Requiere revisión

Abrir auditoría completa Ver informe de evaluación

Dependency or permission surface needs review
Permission surface may require sandboxing
The SKILL.md references external files (references/*.md) that are not fully included in the excerpt, but the repository appears to contain them. This is acceptable as long as the full skill is distributed with those files.
The shared context file .a2a-context.json is a single point of failure; while atomic read-modify-write is specified, concurrent agents could still race if not strictly serialized. The protocol relies on the coordinator to enforce ordering, which is a design assumption.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 287 stars, 43 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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Resultados: —

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Más detalles

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    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20agent-to-agent%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/onewave-ai-agent-to-agent/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/onewave-ai-agent-to-agent"
  }
}

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Creador: OneWave-AI
Fuente: OneWave-AI/claude-skills
Indexado por: Índice comunitario de OpenAgentSkill

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