Multi-Agent Orchestration with Claude: Coordinators and Subagents

Multi-agent systems split a large job across specialised agents. The exam focuses on the coordinator–subagent pattern used by the Claude Agent SDK, and on the mistakes that make such systems produce incomplete or unattributed results (Task Statements 1.2 and 1.3).

🕸️ Hub-and-spoke architecture

A coordinator agent decomposes the task, decides which subagents to invoke, delegates, aggregates results and handles errors. Subagents never talk to each other directly — every message goes through the coordinator. That gives you observability, consistent error handling and controlled information flow.

• Select subagents per query. A simple factual question should not run the full search → analysis → synthesis → report pipeline.
• Partition the scope. Give each subagent distinct subtopics or source types so work isn’t duplicated.
• Refine iteratively. The coordinator checks the synthesis for gaps, re-delegates targeted queries, and re-runs synthesis until coverage is sufficient.

🤖 Spawning subagents in the Agent SDK

• Subagents are spawned with the Task tool. The coordinator’s allowedTools must include "Task", or it cannot delegate.
• Each subagent type is configured with an AgentDefinition: a description, a system prompt and tool restrictions.
• To run subagents in parallel, the coordinator emits several Task calls in one response — not one per turn.

🤖 Subagents start with an empty context

Subagents do not inherit the coordinator’s conversation and don’t share memory between invocations. Anything a subagent needs must be in its prompt.

{
  "task": "Synthesise findings on EU battery regulation",
  "quality_bar": "Two independent sources per claim; flag conflicts",
  "findings": [
    {"claim": "Battery passport required from Feb 2027",
     "excerpt": "...",
     "source_url": "https://example.org/reg",
     "published": "2025-08-14"}
  ]
}

Structured data that separates content from metadata (URL, document, page, date) keeps attribution intact across handoffs. Write coordinator prompts as goals and quality criteria, not step-by-step procedures, so subagents can adapt to what they find.

🧪 Exam-Style Practice Questions

Try these before opening the answers. They use the same scenario style as the real exam.

Question 1. A research report on "renewable energy policy" covers only solar subsidies. Every subagent completed its assignment successfully. Coordinator logs show the subtasks "solar tax credits", "solar feed-in tariffs" and "rooftop solar rebates". What's the root cause?

• A. The analysis agent filters out wind sources
• B. The synthesis agent drops content
• C. The search agent's queries are too narrow
• D. The coordinator's decomposition was too narrow

Question 2. A subagent receives the task "Synthesise the findings" and produces generic text. Why?

• A. It needs `context: fork`
• B. Subagents can't read JSON
• C. Its model is too small
• D. It doesn't automatically inherit the coordinator's history, so the findings must be in its prompt

Question 3. A subagent should run in parallel with two others. Where do the three Task calls go?

• A. In three consecutive coordinator turns
• B. In separate sessions started by a cron job
• C. In a single coordinator response
• D. In a batch request

📝 Assignment

Do these tasks in order. Each one has a Done when check, so you know when it is complete. The stretch task is optional but close to what the exam expects from an architect. Keep your answers in one notes file or Git repository, and revisit them in your final week of revision together with the cheat sheet in the last lesson of this course.

1. Task 1: Sketch a coordinator with three subagents for a research task and list the tools each subagent gets (no more than five).
   ✅ Done when: Every subagent has a one-line role and no more than five tools, and no tool is given to a subagent that does not need it.
2. Task 2: Write the JSON you would pass to a synthesis subagent, including claim, excerpt, source URL and date for two findings.
   ✅ Done when: Your JSON keeps content and metadata in separate fields, so a synthesis agent could cite each claim correctly.
3. Stretch: write a coordinator prompt that states goals and quality criteria without step-by-step instructions.
   ✅ Done when: Your coordinator prompt states the goal and at least three quality criteria, and contains no numbered step-by-step instructions.

❓ Frequently Asked Questions

🤔 Do subagents see the coordinator's conversation?

No. Subagents start with isolated context, so the coordinator must put everything they need in their prompt.

🤔 How do I run subagents in parallel?

Have the coordinator emit several Task tool calls in a single response instead of one per turn.

🤔 Why route everything through the coordinator?

It gives you observability, consistent error handling and control over what information each agent sees.

🤔 What causes a report to miss whole topics?

Usually the coordinator decomposed the topic too narrowly, even though each subagent completed its own task.

🏁 Summary

• All communication flows through the coordinator.
• "Task" must be in the coordinator’s allowedTools; parallel = multiple Task calls in one turn.
• Pass context explicitly, as structured data with source metadata.
• Missing coverage with “successful” subagents → narrow decomposition.

Next, continue with Claude Agent SDK Hooks, Prerequisite Gates and Human Handoffs.

Independent study material by SQA Tools. Not affiliated with, endorsed by or sponsored by Anthropic. Claude is a trademark of Anthropic. Mock questions are original practice items, not real exam content. Exam facts checked against Anthropic's official exam guides and certification FAQ on 11 November 2026.