Latest AI Techniques: RAG, Tool Use, Agents & MCPThe Model Context Protocol (MCP) and open agent standards · Lesson 17 of 20

The open agent standards: A2A, Agent Skills and AGENTS.md

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The open agent standards: A2A, Agent Skills and AGENTS.md

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The open agent standards

  • MCP • A2A • Agent Skills • AGENTS.md
  • Which layer each covers
  • Write your first skill

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Chapters

The open standards stack for agents

A year ago, every agent platform had its own way of connecting tools, describing skills and talking to other agents. That is changing fast. Several open standards now cover different layers of the problem, and knowing which does what saves you from building the same integration three times.

LayerStandardWhat it standardisesGovernance (at the time of writing)
Agent to tools and dataModel Context Protocol (MCP)How AI apps connect to tools, resources and promptsAgentic AI Foundation (Linux Foundation)
Agent to agentAgent2Agent (A2A)How independent agents discover each other, exchange messages and hand off tasksLinux Foundation project (contributed by Google)
Reusable know-howAgent SkillsPackaging instructions, scripts and resources as folders an agent loads when relevantOpen specification (originated at Anthropic)
Repository guidanceAGENTS.mdA predictable file where coding agents find project-specific instructionsAgentic AI Foundation (contributed by OpenAI)

These are complementary: an agent might load a skill (how to prepare our monthly client report), call MCP tools (fetch analytics, create a draft in the CRM), and delegate a sub-task to a partner's agent over A2A (ask the media-buying agency's agent for spend data).

Agent2Agent (A2A)

MCP connects an agent to tools; A2A connects agents to other agents, typically across organisational or vendor boundaries, where neither side should expose its internal tools, memory or prompts. Core ideas:

  • Agent Card: a machine-readable description that an agent publishes (its name, what it can do, how to reach it, what authentication it needs), so other agents can discover it.
  • Tasks: units of work with a lifecycle (submitted, working, input required, completed, failed) and results delivered as messages and artefacts, with streaming and asynchronous updates for long jobs.
  • Opacity: each agent stays a black box; they collaborate through the protocol without sharing internals.

A2A reached a 1.0 release in early 2026 and is supported by major cloud platforms. Use it when you genuinely need to delegate to an agent you do not control (a supplier's, a partner's, another department's). Inside your own system, ordinary function calls or sub-agents are simpler.

Agent Skills

A skill is a folder containing a SKILL.md file (YAML front matter with at least a name and description, then Markdown instructions), plus optional scripts, reference documents and assets. The key idea is progressive disclosure: an agent initially sees only each skill's name and description (a few dozen tokens each); when a task matches, it loads the full instructions, and only opens the bundled files it needs. That lets an agent have access to many skills without flooding its context.

---
name: monthly-client-report
description: Prepare the agency's monthly performance report for a client from exported GA4 and ad-platform CSVs. Use when asked for a monthly report, performance summary or client recap.
---

# Monthly client report

1. Load the CSVs the user provides. Compute metrics ONLY with scripts/metrics.py (never in your head).
2. Compare with last month and the same month last year if available.
3. Write the report using templates/report.md: summary (5 bullets), wins, issues, hypotheses, next tests.
4. Label every hypothesis as a hypothesis. Never state causes as facts.
5. Flag any metric that moved more than 25% for human review before sending.

Anthropic published Agent Skills as an open standard in December 2025, and it has since been adopted by many agent products and coding tools. Because skills can include executable scripts, treat third-party skills like third-party code: review them, pin versions and run them in a sandbox.

AGENTS.md

For software teams, AGENTS.md is a plain Markdown file at the root of a repository that tells coding agents how to work there: build and test commands, code style, architecture notes, "never do" rules. It is deliberately simple and is read by many coding agents; some tools also read their own files (for example CLAUDE.md), so teams often keep one source of truth and reference it from the others.

# AGENTS.md
## Setup
- Install: `npm ci`  | Test: `npm test` | Lint: `npm run lint`
## Conventions
- TypeScript strict mode; no `any`. API handlers live in `src/api/`.
## Never
- Never commit secrets or edit files under `migrations/` by hand.

How the standards fit together: worked example

A Dubai-based e-commerce agency builds an "account manager assistant":

  1. Skills hold the agency's playbooks: monthly report, campaign post-mortem, new-client onboarding checklist.
  2. MCP servers connect it to GA4 exports in cloud storage, the CRM and the project tool; write tools create drafts only.
  3. A2A is used for one partner: a media-buying partner exposes an agent that answers "spend and ROAS by campaign for client X, last month", without giving the agency access to its ad accounts.
  4. The engineers who maintain the internal tooling keep an AGENTS.md in each repository so their coding agents follow the same conventions.

Each standard solved a distinct problem; none of them replaced good design, least privilege or evaluation.

Hands-on: write and test your first skill

  1. Pick a task you repeat monthly (a report, a proposal section, a QA checklist).
  2. Create a folder my-skill/ with SKILL.md: a precise name and a description that says what it does and when to use it (this is what the agent sees before loading it).
  3. Add numbered steps, quality rules and "never" rules. Move long reference material into separate files the instructions point to.
  4. If a step needs exact computation or formatting, add a small script and tell the skill to use it.
  5. Load it in a tool that supports Agent Skills, try five realistic requests (including one that should not trigger it) and refine the description until triggering is reliable.

Key takeaways

  • MCP connects agents to tools and data; A2A connects agents to other agents; Agent Skills package know-how; AGENTS.md guides coding agents.
  • A2A uses Agent Cards for discovery and task lifecycles for delegation, keeping each agent opaque.
  • Skills use progressive disclosure: name and description first, full instructions and files only when relevant.
  • Open standards reduce integration work but do not replace design, least privilege, sandboxing or evaluation.

Check your understanding

Quick questions to lock in the lesson. They don’t count towards your certificate.

  1. Your agency needs its assistant to request spend data from a partner’s agent without accessing the partner’s ad accounts. Which standard fits?
  2. What does an agent see about a skill before deciding to load it?
  3. Why treat third-party skills like third-party code?

Put it into practice

Write a SKILL.md for one repeated task in your work, test it with five requests (one that should not trigger it), and note which of MCP, A2A or AGENTS.md your setup would also need.

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