dispatching-parallel-agents

Dispatching Parallel Agents

Overview

When multiple unrelated failures or tasks exist (different test files, different subsystems, different bugs), investigating them sequentially wastes time. Each investigation is independent and can happen in parallel.

Core principle: Dispatch one agent per independent problem domain. Let them work concurrently.

When to Use

Use when:

• 3+ test files failing with different root causes
• Multiple subsystems broken independently
• Each problem can be understood without context from others
• No shared state between investigations

Don't use when:

• Failures are related (fix one might fix others)
• Agents would interfere with each other (editing same files)
• Still in exploration phase

The Pattern

1. Identify Independent Domains

Group failures by what's broken. Each domain is independent.

2. Create Focused Agent Tasks

Each agent gets:

• Specific scope: One test file or subsystem
• Clear goal: Make these tests pass
• Constraints: Don't change other code
• Expected output: Summary of what you found and fixed

3. Dispatch in Parallel

All agents run concurrently via the Agent tool.

4. Review and Integrate

When agents return: verify fixes don't conflict, run full test suite, integrate all changes.

Good Agent Prompt Structure

1. Focused — One clear problem domain
2. Self-contained — All context needed to understand the problem
3. Specific about output — What should the agent return?

Example:

Fix the 3 failing tests in src/agents/agent-tool-abort.test.ts:
1. "should abort tool with partial output capture" - expects 'interrupted at' in message
2. "should handle mixed completed and aborted tools" - fast tool aborted instead of completed

Root cause likely: timing/race condition issues.
Return: Summary of what you found and what you fixed.

Common Mistakes

Verification After Agents Return

1. Read each summary — understand what changed
2. Check for conflicts — did agents edit same code?
3. Run full suite — verify all fixes work together
4. Spot check — agents can make systematic errors