
Dispatching Parallel Agents
FreeMaximize efficiency by solving multiple independent tasks concurrently.
Free · Opens the source repo
What Dispatching Parallel Agents does
Dispatching Parallel Agents is a skill designed for developers and engineers who need to efficiently handle multiple independent tasks that can be executed without shared state or dependencies. This skill allows you to delegate specific tasks to specialized agents, each operating in isolation. By crafting precise instructions and context for each agent, you ensure that they remain focused on their individual tasks, which preserves your own context for higher-level coordination. This approach is particularly useful when dealing with multiple unrelated failures, such as different test files or subsystems that require investigation.
The core principle of this skill is to dispatch one agent per independent problem domain, allowing them to work concurrently. For instance, if you encounter several test failures across different files that do not affect one another, you can assign each failure to a separate agent. This parallel execution not only saves time but also enhances productivity, as each agent can work on its task simultaneously without waiting for others to complete their investigations.
To effectively utilize this skill, you should first identify independent domains by grouping failures based on what is broken. Next, you create focused tasks for each agent, specifying the scope, goals, and expected outputs. Once the tasks are defined, you can dispatch them in parallel, allowing all agents to work concurrently. After they return with their findings, you can review their summaries, verify that there are no conflicts, and integrate the changes seamlessly.
This skill is particularly beneficial in scenarios where you have multiple failures that can be understood independently, such as when testing different features or components of a system. However, it is essential to avoid using this skill when failures are related, as fixing one may resolve others, or when a comprehensive understanding of the entire system state is required.
When to use it
Use this skill when facing multiple unrelated failures that can be addressed independently, such as different test files or subsystems.
When not to use it
Avoid using this skill when failures are related, require a full system context, or when agents may interfere with one another.
What you can build with it
Multiple Test Failures
You have 6 test failures across 3 files after a major refactor, each failure is independent and can be fixed concurrently.
Subsystem Investigations
Different subsystems are broken independently, allowing you to assign each to a separate agent for focused investigation.
Parallel Debugging
You need to debug several unrelated bugs at once, using parallel agents to maximize efficiency and reduce time spent.
How to install Dispatching Parallel Agents
View source1. Install with the skills CLI
npx skills add obra/superpowers/dispatching-parallel-agents --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by obraDispatching Parallel Agents
Overview
You delegate tasks to specialized agents with isolated context. By precisely crafting their instructions and context, you ensure they stay focused and succeed at their task. They should never inherit your session's context or history — you construct exactly what they need. This also preserves your own context for coordination work.
When you have multiple unrelated failures (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
digraph when_to_use {
"Multiple failures?" [shape=diamond];
"Are they independent?" [shape=diamond];
"Single agent investigates all" [shape=box];
"One agent per problem domain" [shape=box];
"Can they work in parallel?" [shape=diamond];
"Sequential agents" [shape=box];
"Parallel dispatch" [shape=box];
"Multiple failures?" -> "Are they independent?" [label="yes"];
"Are they independent?" -> "Single agent investigates all" [label="no - related"];
"Are they independent?" -> "Can they work in parallel?" [label="yes"];
"Can they work in parallel?" -> "Parallel dispatch" [label="yes"];
"Can they work in parallel?" -> "Sequential agents" [label="no - shared state"];
}
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)
- Need to understand full system state
- Agents would interfere with each other
The Pattern
1. Identify Independent Domains
Group failures by what's broken:
- File A tests: Tool approval flow
- File B tests: Batch completion behavior
- File C tests: Abort functionality
Each domain is independent - fixing tool approval doesn't affect abort tests.
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
Issue all three subagent dispatches in the same response — they run in parallel:
Subagent (general-purpose): "Fix agent-tool-abort.test.ts failures"
Subagent (general-purpose): "Fix batch-completion-behavior.test.ts failures"
Subagent (general-purpose): "Fix tool-approval-race-conditions.test.ts failures"
# All three run concurrently.
Multiple dispatch calls in one response = parallel execution. One per response = sequential.
4. Review and Integrate
When agents return:
- Read each summary
- Verify fixes don't conflict
- Run full test suite
- Integrate all changes
Agent Prompt Structure
Good agent prompts are:
- Focused - One clear problem domain
- Self-contained - All context needed to understand the problem
- Specific about output - What should the agent return?
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
3. "should properly track pendingToolCount" - expects 3 results but gets 0
These are timing/race condition issues. Your task:
1. Read the test file and understand what each test verifies
2. Identify root cause - timing issues or actual bugs?
3. Fix by:
- Replacing arbitrary timeouts with event-based waiting
- Fixing bugs in abort implementation if found
- Adjusting test expectations if testing changed behavior
Do NOT just increase timeouts - find the real issue.
Return: Summary of what you found and what you fixed.
Common Mistakes
❌ Too broad: "Fix all the tests" - agent gets lost ✅ Specific: "Fix agent-tool-abort.test.ts" - focused scope
❌ No context: "Fix the race condition" - agent doesn't know where ✅ Context: Paste the error messages and test names
❌ No constraints: Agent might refactor everything ✅ Constraints: "Do NOT change production code" or "Fix tests only"
❌ Vague output: "Fix it" - you don't know what changed ✅ Specific: "Return summary of root cause and changes"
When NOT to Use
Related failures: Fixing one might fix others - investigate together first Need full context: Understanding requires seeing entire system Exploratory debugging: You don't know what's broken yet Shared state: Agents would interfere (editing same files, using same resources)
Real Example from Session
Scenario: 6 test failures across 3 files after major refactoring
Failures:
- agent-tool-abort.test.ts: 3 failures (timing issues)
- batch-completion-behavior.test.ts: 2 failures (tools not executing)
- tool-approval-race-conditions.test.ts: 1 failure (execution count = 0)
Decision: Independent domains - abort logic separate from batch completion separate from race conditions
Dispatch:
Agent 1 → Fix agent-tool-abort.test.ts
Agent 2 → Fix batch-completion-behavior.test.ts
Agent 3 → Fix tool-approval-race-conditions.test.ts
Results:
- Agent 1: Replaced timeouts with event-based waiting
- Agent 2: Fixed event structure bug (threadId in wrong place)
- Agent 3: Added wait for async tool execution to complete
Integration: All fixes independent, no conflicts, full suite green
Verification
After agents return:
- Review each summary - Understand what changed
- Check for conflicts - Did agents edit same code?
- Run full suite - Verify all fixes work together
- Spot check - Agents can make systematic errors
Frequently asked questions about Dispatching Parallel Agents
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