Skills obra/superpowers Superpowers
dispatching-parallel-agents
- Use it when
- you have two or more problems that don't share state, such as test failures in unrelated files
- It does
- gives each problem its own subagent with a focused, self-contained prompt, and starts them all at once
- You get
- one summary per subagent, checked for conflicts and confirmed by a run of the full test suite
- Not for
- related failures, exploratory debugging, or subagents that would edit the same files
- Unlike subagent-driven-development
- which runs a written plan one task at a time; here there's no plan and the subagents work side by side
Skill 13 of 14 in the Superpowers bundle · Before it: verification-before-completion · After it: writing-skills
TLDR
When failures have different causes, investigating them one after another wastes time. The agent groups them by what's broken, such as one test file or subsystem each, and writes each subagent a prompt with a single scope, the error messages and test names, limits such as "don't change production code", and what to report back. It starts them all at once. When they return, it reads each summary, checks that no two touched the same code, runs the whole suite, and spot-checks the fixes, since several subagents can repeat the same kind of mistake. The skill walks through a real case: six failures across three files, fixed by three subagents with no conflicts.
Summarizes the skill at bb92a77.
npx skills add https://github.com/obra/superpowers --skill dispatching-parallel-agentsskills.sh page · Source on GitHub · All skills from obra/superpowers
- Installs
- 195,735 on skills.sh, Sep 21, 2026
- Repo stars
- 289,267 obra/superpowers
- First seen
- Jan 19, 2026 on skills.sh
Weekly values
| Week to | Installs |
|---|---|
| Aug 3 | 6,486 |
| Aug 10 | 6,071 |
| Aug 17 | 5,813 |
| Aug 24 | 7,019 |
| Aug 31 | 5,716 |
| Sep 7 | 5,912 |
| Sep 14 | 5,835 |
| Sep 21 | 5,827 |
| Category |
Test-first work, implementation from specs, git hygiene and scope control. Build agents, orchestrate workers and give agents memory. Everything for building software: planning, coding, debugging, design, frameworks, cloud, agents and skills. |
|---|---|
| Type |
A multi-step process the agent follows: interview, debug, run a TDD loop, review. |
| Effect |
Its own steps create or change files, git state or local tools. |
| Needs |
Relies on the agent being able to spawn subagents. |
| Publisher |
Everyone else. Unverified vendor claims default to community. |
| Topics |
SKILL.md
From obra/superpowers at bb92a77. Checked daily, last changed Oct 20, 2026.
Frontmatter
name: dispatching-parallel-agents
description: Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependenciesDispatching 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