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A2a Agent Protocol Expert

Community
roedyrustam
a2a-agent-protocol-expert

A2A agent protocol interoperability, Agent Cards, and MCP bridging / Protokol agen A2A, Agent Cards, dan integrasi MCP.

Overview

Publisherroedyrustam
Repositoryvibes-plug
Skill namea2a-agent-protocol-expert
Stars
117
Forks
27
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by roedyrustam on GitHub. Read the source before you install it.

Installation

Install the A2a Agent Protocol Expert AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/roedyrustam/vibes-plug/tree/main/skills/a2a-agent-protocol-expert
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/roedyrustam/vibes-plug.git /tmp/vibes-plug
mkdir -p .claude/skills
cp -r /tmp/vibes-plug/skills/a2a-agent-protocol-expert .claude/skills/a2a-agent-protocol-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable A2a Agent Protocol Expert in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads A2a Agent Protocol Expert on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so A2a Agent Protocol Expert is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent-to-Agent (A2A) Protocol & Federated Swarm Expert (2026 Edition)

English | Bahasa Indonesia


English

Orchestration & Integration

  • Multi-Agent & MCP Ecosystem: multi-agent-orchestration, mcp-server-architect, mcp-sampling-critic, parallel-tool-orchestrator, durable-agent-execution-expert, computer-use-os-agent-expert
  • Agentic Economy & Settlement: agentic-m2m-settlement, agentic-micro-economy-architect, doku-mcp-server
  • Security & Contracts: structured-output-contracts, prompt-injection-firewall, zero-trust-secret-vault
  • Lifecycle & Governance: brainstorming, zero-to-prod-orchestrator, session-memory-manager

Description

Production guide for implementing the open Agent-to-Agent (A2A) Protocol alongside Model Context Protocol (MCP). While MCP connects an agent to deterministic tools and resources (Agent-to-Tool), A2A enables opaque autonomous agents built on different frameworks (LangGraph, Pydantic AI, Google ADK, OpenAI Agents SDK, Mastra) to discover capabilities via /.well-known/agent.json Agent Cards, negotiate multi-turn tasks (tasks/send, tasks/sendSubscribe), exchange typed Artifacts, and settle M2M budgets.

Trigger Conditions

  • Exposing an autonomous agent service to external partner agents via standard HTTP JSON-RPC + SSE.
  • Publishing or consuming /.well-known/agent.json Agent Cards for dynamic capability discovery.
  • Orchestrating cross-organization or polyglot multi-agent workflows where subagents do not share internal memory.
  • Combining A2A horizontal agent delegation with MCP vertical tool execution.

A2A vs MCP Architectural Separation

DimensionModel Context Protocol (MCP v1.x)Agent-to-Agent Protocol (A2A)
Primary RelationshipAgent $\leftrightarrow$ Deterministic Tool / ResourceClient Agent $\leftrightarrow$ Remote Autonomous Agent
Discovery Mechanismtools/list, resources/list, prompts/listGET /.well-known/agent.json (Agent Card)
Execution LifecycleSynchronous RPC call (tools/call)Stateful Task lifecycle (submitted $\rightarrow$ working $\rightarrow$ input-required $\rightarrow$ completed)
State & ReasoningStateless function executionOpaque internal reasoning, memory, and multi-step planning

Core Implementation Patterns

1. Standard /.well-known/agent.json Agent Card Specification
typescript
// src/a2a/agent-card.ts
export interface A2AAgentSkill {
  id: string;
  name: string;
  description: string;
  tags: string[];
  inputModes: ('text/plain' | 'application/json')[];
  outputModes: ('text/plain' | 'application/json')[];
}

export interface A2AAgentCard {
  name: string;
  description: string;
  url: string;
  version: string;
  capabilities: {
    streaming: boolean;
    pushNotifications: boolean;
    stateTransitionHistory: boolean;
  };
  authentication: {
    schemes: ('Bearer' | 'OAuth2' | 'MutualTLS')[];
  };
  skills: A2AAgentSkill[];
}

export const FINTECH_AUDITOR_AGENT_CARD: A2AAgentCard = {
  name: 'vibes-fintech-auditor',
  description: 'Autonomous SNAP BI payment reconciliation and Z3 invariant verifier agent',
  url: 'https://agents.internal.example.com/a2a/fintech-auditor',
  version: '4.4.2',
  capabilities: {
    streaming: true,
    pushNotifications: true,
    stateTransitionHistory: true,
  },
  authentication: {
    schemes: ['Bearer'],
  },
  skills: [
    {
      id: 'verify-settlement-batch',
      name: 'Verify Settlement Batch',
      description: 'Audits DOKU SNAP BI webhook records against double-entry ledger postings',
      tags: ['fintech', 'doku', 'ledger', 'audit'],
      inputModes: ['application/json'],
      outputModes: ['application/json'],
    },
  ],
};

2. A2A JSON-RPC Task Handler (tasks/send & State Machine)
typescript
// src/a2a/task-router.ts
import { Hono } from 'hono';
import { z } from 'zod';
import { FINTECH_AUDITOR_AGENT_CARD } from './agent-card';

const app = new Hono();

const TaskSendSchema = z.object({
  jsonrpc: z.literal('2.0'),
  id: z.union([z.string(), z.number()]),
  method: z.enum(['tasks/send', 'tasks/get', 'tasks/cancel']),
  params: z.object({
    id: z.string().uuid(),
    sessionId: z.string().optional(),
    message: z.object({
      role: z.enum(['user', 'agent']),
      parts: z.array(
        z.object({
          type: z.enum(['text', 'data']),
          text: z.string().optional(),
          data: z.record(z.unknown()).optional(),
        })
      ),
    }),
  }),
});

app.get('/.well-known/agent.json', (c) => c.json(FINTECH_AUDITOR_AGENT_CARD));

app.post('/a2a/fintech-auditor', async (c) => {
  const body = await c.req.json();
  const parsed = TaskSendSchema.safeParse(body);
  if (!parsed.success) {
    return c.json({
      jsonrpc: '2.0',
      id: body?.id ?? null,
      error: { code: -32602, message: 'Invalid A2A task parameters', data: parsed.error.issues },
    }, 400);
  }

  const { id: rpcId, params } = parsed.data;

  return c.json({
    jsonrpc: '2.0',
    id: rpcId,
    result: {
      id: params.id,
      status: {
        state: 'completed',
        timestamp: new Date().toISOString(),
      },
      artifacts: [
        {
          name: 'audit-verdict.json',
          parts: [
            {
              type: 'data',
              data: { verified: true, discrepanciesFound: 0, taskId: params.id },
            },
          ],
        },
      ],
    },
  });
});

export default app;

3. A2A Streaming Task SSE Protocol (tasks/sendSubscribe) with Heartbeats (TypeScript)

Real-time state streaming and token emission for long-running federated agent tasks:

typescript
// src/a2a/streaming-sse-handler.ts
export interface A2ATaskEvent {
  taskId: string;
  eventType: 'state_changed' | 'token_stream' | 'artifact_published' | 'heartbeat';
  state?: 'working' | 'input-required' | 'completed' | 'failed';
  chunk?: string;
  artifactUri?: string;
  timestamp: string;
}

export function formatA2aSseFrame(event: A2ATaskEvent): string {
  return `event: a2a_event\ndata: ${JSON.stringify(event)}\n\n`;
}

export class A2aStreamingSession {
  private readonly taskId: string;
  private isClosed = false;

  constructor(taskId: string) {
    this.taskId = taskId;
  }

  public emitHeartbeat(): string {
    return formatA2aSseFrame({
      taskId: this.taskId,
      eventType: 'heartbeat',
      timestamp: new Date().toISOString(),
    });
  }

  public emitTokenChunk(chunk: string): string {
    return formatA2aSseFrame({
      taskId: this.taskId,
      eventType: 'token_stream',
      chunk,
      timestamp: new Date().toISOString(),
    });
  }

  public emitCompletion(artifactUri: string): string {
    this.isClosed = true;
    return formatA2aSseFrame({
      taskId: this.taskId,
      eventType: 'artifact_published',
      state: 'completed',
      artifactUri,
      timestamp: new Date().toISOString(),
    });
  }
}

Verification Checklist

  • Agent service publishes a valid /.well-known/agent.json endpoint declaring authentication schemes and typed skills.
  • All A2A task states adhere to standard transitions (submitted $\rightarrow$ working $\rightarrow$ input-required | completed | failed | canceled).
  • Incoming parts payloads from remote agents are validated via Zod schemas and sanitized through prompt-injection-firewall.
  • Long-running tasks support SSE streaming (tasks/sendSubscribe) or signed webhook push notifications.

Sovereign Execution, Token Efficiency & Invariants

DimensionSovereign Mandate & Deterministic Contract
Frontier Model CascadeMedium / High (GPT-5.6 Sol Medium, Gemini 4 Argon, Claude Sonnet 5.5 High, Grok 4.7 High Fast)
Availability FallbackGemini 4 Argon/Pro -> Gemini 3.8 Flash; Claude Opus 5.5 -> Claude Opus 4.6 (Zero unhandled missing-model errors)
KV-Cache & Token ProtocolPin static instructions & schemas at prompt prefix (kv-cache-prefix-optimizer); pass surgical CONTEXT_MAP.md slices (<250 tokens/call) during Swarm Fan-Out
SaaT CLI & MCP DispatchCLI: vibes skill exec a2a-agent-protocol-expert <audit|eval|verify|generate|blueprint> / MCP: vibes_skill_dispatch, vibes_ast_query, vibes_compile_cache, vibes_optimize_budget, vibes_verify_gate
NFR & Anti-Slop InvariantsP99 API Gateway Latency < 85ms, OpenAPI 3.1 / TypeSpec strict schema parity, RFC 9457 Problem Details error contracts, Idempotency-Key enforcement; 100% complete zero-placeholder output verified via node scripts/check-anti-slop.js --strict


Bahasa Indonesia

Integrasi Orkestrasi

  • Ekosistem Multi-Agen & MCP: multi-agent-orchestration, mcp-server-architect, mcp-sampling-critic, parallel-tool-orchestrator, durable-agent-execution-expert, computer-use-os-agent-expert
  • Ekonomi & Settlement Agen: agentic-m2m-settlement, agentic-micro-economy-architect, doku-mcp-server
  • Keamanan & Kontrak: structured-output-contracts, prompt-injection-firewall, zero-trust-secret-vault
  • Siklus Hidup & Tata Kelola: brainstorming, zero-to-prod-orchestrator, session-memory-manager

Deskripsi

Panduan produksi untuk mengimplementasikan Agent-to-Agent (A2A) Protocol berdampingan dengan Model Context Protocol (MCP). Jika MCP menghubungkan agen ke tool deterministik (Agent-to-Tool), A2A memungkinkan agen otonom lintas framework untuk saling menemukan kapabilitas melalui /.well-known/agent.json (Agent Card), menegosiasikan tugas multi-giliran (tasks/send), dan bertukar Artifact terstruktur.

Panduan Arsitektur Inti

  1. Sinergi A2A + MCP: Gunakan A2A untuk delegasi horizontal antar-agen spesialis, dan gunakan MCP untuk pemanggilan fungsi/tool vertikal di dalam masing-masing agen.
  2. Penemuan Dinamis (Agent Card): Publikasikan kapabilitas, mode input/output, dan skema autentikasi di /.well-known/agent.json.
  3. Pertahanan Injeksi Lintas-Agen: Perlakukan setiap pesan dari agen eksternal sebagai input yang tidak tepercaya; validasi dengan skema JSON ketat dan prompt-injection-firewall.

Daftar Periksa Verifikasi (Checklist)

  • Endpoint /.well-known/agent.json tersedia dan mendeklarasikan skema autentikasi.
  • Siklus hidup tugas mengikuti status standar (submitted, working, input-required, completed, failed).
  • Payload antar-agen divalidasi dengan Zod dan disanitasi dari serangan indirect prompt injection.

Matriks Eksekusi Berdaulat, Efisiensi Token & Invarian

DimensiMandat Berdaulat & Kontrak Deterministik
Kaskade Model FrontierMedium / High (GPT-5.6 Sol Medium, Gemini 4 Argon, Claude Sonnet 5.5 High, Grok 4.7 High Fast)
Invarian Fallback KetersediaanGemini 4 Argon/Pro -> Gemini 3.8 Flash; Claude Opus 5.5 -> Claude Opus 4.6 (Bebas gagal saat model belum tersedia/kuota penuh)
Protokol Hemat Token & KV-CacheKunci instruksi & skema statis di prefix awal (kv-cache-prefix-optimizer); kirim potongan CONTEXT_MAP.md (<250 token/panggilan) saat Fan-Out
Eksekusi SaaT CLI & MCPCLI: vibes skill exec a2a-agent-protocol-expert <audit|eval|verify|generate|blueprint> / MCP: vibes_skill_dispatch, vibes_ast_query, vibes_compile_cache, vibes_optimize_budget, vibes_verify_gate
Invarian NFR & Anti-SlopLatensi P99 API < 85ms, paritas skema ketat OpenAPI 3.1 / TypeSpec, kontrak error RFC 9457 Problem Details, penegakan Idempotency-Key; kode 100% tuntas tanpa placeholder diverifikasi melalui node scripts/check-anti-slop.js --strict

Frequently asked questions

What does the A2a Agent Protocol Expert AI skill do?

A2A agent protocol interoperability, Agent Cards, and MCP bridging / Protokol agen A2A, Agent Cards, dan integrasi MCP.

Why use A2a Agent Protocol Expert on TypingMind?

Because you install it once and use it with any model. A2a Agent Protocol Expert is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install A2a Agent Protocol Expert in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/roedyrustam/vibes-plug/tree/main/skills/a2a-agent-protocol-expert. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use A2a Agent Protocol Expert?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with A2a Agent Protocol Expert?

As many as you like. As long as a model supports skills, you can use A2a Agent Protocol Expert with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the A2a Agent Protocol Expert AI skill free?

Yes. It is published on GitHub by roedyrustam under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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