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When to spawn agents vs work directly - parallel execution, specialization
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/ktg-one/assetswap --skill agent-patterns명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | agent-patterns |
| description | When to spawn agents vs work directly - parallel execution, specialization |
| allowed-tools | Read, Bash, Task |
| model | sonnet |
Spawn smart, not often.
"Search for auth bugs"
→ Spawn 5 agents, one per module
→ 5x faster, same tokens
"Review this PR"
→ security-agent
→ performance-agent
→ style-agent
Each has focused expertise
❌ Agent 1 creates file
❌ Agent 2 needs that file
= Race condition, wasted tokens
✓ Do sequentially in main conversation
❌ "Spawn agent to add one line"
= Overhead > benefit
✓ Just do it directly
Task tool with subagent_type=Explore
- Fast file/code search
- Codebase questions
- Pattern finding
Task tool with subagent_type=general-purpose
- Multi-step implementation
- Complex changes
- Autonomous work
code-reviewer: Style, bugs, patterns
debugger: Error investigation
security-reviewer: Vulnerability scan
performance-reviewer: Bottleneck analysis
Single message, multiple Task calls:
Task 1: "Search auth module for bugs"
Task 2: "Search payment module for bugs"
Task 3: "Search user module for bugs"
Task 4: "Search api module for bugs"
Task 5: "Search data module for bugs"
All run simultaneously.
run_in_background: true
Start long-running work →
Continue other tasks →
Check results later with TaskOutput
Main conversation: Full codebase context
Agent: Only sees what it needs
"Search auth/"
Agent loads only auth/, not entire codebase.
Agent does extensive search →
Returns: "Found issue in auth.swift:142"
You get 1-line summary, not full exploration.
Tokens saved: 90%+
1. Explore agent finds the problem
2. Main conversation receives summary
3. You fix directly with focused context
No need to spawn another agent.
❌ "Spawn agent for each file"
= 50 agents for 50 files = chaos
✓ "Spawn agent per module" (5-10 agents)
❌ "Spawn agent to read config.json"
= 10 seconds + overhead
✓ Read tool directly = instant
❌ Spawn → Wait → Spawn → Wait
✓ Spawn all → Work on other things → Collect results
| Task | Agents | Why |
|---|---|---|
| Bug search | 5-10 | One per major module |
| PR review | 3-4 | Security, perf, style, tests |
| Refactor | 2-3 | Analyzer, transformer, validator |
| Feature build | 4 | UI, logic, tests, docs |
| Codebase exploration | 1 | Single thorough search |
Task tool with resume: "agent-id"
Agent continues with full prior context.
No need to re-explain.
Resume: Same task, more work needed
New: Different task, fresh context
# In skill frontmatter or Task call
model: haiku # Simple searches, formatting
model: sonnet # Code review, implementation
model: opus # Architecture, complex reasoning
Default to cheapest model that works.
Use when: Parallel work, specialized tasks, large codebase operations