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여러 작업을 동시에 진행해도 되는지 판단하고 범위를 나누는 스킬입니다. 단순히 인원을 늘리는 것보다 서로의 결과를 기다리지 않는 작업을 구분하는 데 초점이 있습니다.
해야 할 일과 파일·결과 사이의 의존 관계를 알려주세요. 독립된 작업의 경계와 결과를 합칠 기준을 정하면 중복 수정과 충돌을 줄이는 데 도움이 됩니다.
dispatching-parallel-agents · Claude / Claude Code · OpenAI · Codex · Gemini CLI · Grok Build
서로 의존하지 않는 작업을 구분해 병렬 작업 단위로 나눕니다.
여러 작업을 동시에 진행해도 되는지 판단하고 범위를 나누는 스킬입니다. 단순히 인원을 늘리는 것보다 서로의 결과를 기다리지 않는 작업을 구분하는 데 초점이 있습니다.
해야 할 일과 파일·결과 사이의 의존 관계를 알려주세요. 독립된 작업의 경계와 결과를 합칠 기준을 정하면 중복 수정과 충돌을 줄이는 데 도움이 됩니다.
“이 작업 목록에서 독립적으로 진행할 수 있는 항목을 골라줘. 각 작업의 입력, 수정 범위, 완료 결과를 나눠줘.”
받을 수 있는 결과분리된 작업 범위와 취합 기준
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사용하는 환경에 맞는 방법 하나를 선택하세요. Superpowers 전체 패키지를 설치하고 새 세션에서 작업을 요청하면 관련 스킬이 호출됩니다.
Claude Code: /plugin install superpowers@claude-plugins-official Codex 앱: Plugins → Coding → Superpowers 설치 Codex CLI: /plugins → Superpowers → Install Plugin Gemini CLI 터미널: gemini extensions install https://github.com/obra/superpowers
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예상 결과는 ‘분리된 작업 범위와 취합 기준’입니다. 필요한 내용이 포함됐는지 확인하세요. 입력 자료의 사실·숫자와 결과를 대조하고, 부족한 부분을 이어서 요청하세요.
제작자 원본 2026-10-04 확인 · 설치 안내 2026-10-04 확인 · 실제 설치·실행 미검증
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설치 안내 출처---
name: dispatching-parallel-agents
description: Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
---
# Dispatching 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
```dot
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];---
name: dispatching-parallel-agents
description: Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
---
# Dispatching 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
```dot
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:
```text
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:
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?
```markdown
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:
1. **Review 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
Original skill: obra/superpowers/skills/dispatching-parallel-agents/SKILL.md Source: https://github.com/obra/superpowers/blob/8ca22dba9a94f28898bbce59f2537ff4d87c747d/skills/dispatching-parallel-agents/SKILL.md License: MIT MIT License Copyright (c) 2025 Jesse Vincent Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
SKILL.md 본문입니다. 원문에서 참조하는 스크립트·보조 파일은 원본 패키지에 포함되어 있습니다.