parallel-agents
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
Best use case
parallel-agents is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
Teams using parallel-agents should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/parallel-agents-ven0m0/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How parallel-agents Compares
| Feature / Agent | parallel-agents | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Native Parallel Agents > Orchestration through Claude Code's built-in Agent Tool ## Overview This skill enables coordinating multiple specialized agents through Claude Code's native agent system. Unlike external scripts, this approach keeps all orchestration within Claude's control. ## When to Use Orchestration ✅ **Good for:** - Complex tasks requiring multiple expertise domains - Code analysis from security, performance, and quality perspectives - Comprehensive reviews (architecture + security + testing) - Feature implementation needing backend + frontend + database work ❌ **Not for:** - Simple, single-domain tasks - Quick fixes or small changes - Tasks where one agent suffices --- ## Native Agent Invocation ### Single Agent ``` Use the security-auditor agent to review authentication ``` ### Sequential Chain ``` First, use the explorer-agent to discover project structure. Then, use the backend-specialist to review API endpoints. Finally, use the test-engineer to identify test gaps. ``` ### With Context Passing ``` Use the frontend-specialist to analyze React components. Based on those findings, have the test-engineer generate component tests. ``` ### Resume Previous Work ``` Resume agent [agentId] and continue with additional requirements. ``` --- ## Orchestration Patterns ### Pattern 1: Comprehensive Analysis ``` Agents: explorer-agent → [domain-agents] → synthesis 1. explorer-agent: Map codebase structure 2. security-auditor: Security posture 3. backend-specialist: API quality 4. frontend-specialist: UI/UX patterns 5. test-engineer: Test coverage 6. Synthesize all findings ``` ### Pattern 2: Feature Review ``` Agents: affected-domain-agents → test-engineer 1. Identify affected domains (backend? frontend? both?) 2. Invoke relevant domain agents 3. test-engineer verifies changes 4. Synthesize recommendations ``` ### Pattern 3: Security Audit ``` Agents: security-auditor → penetration-tester → synthesis 1. security-auditor: Configuration and code review 2. penetration-tester: Active vulnerability testing 3. Synthesize with prioritized remediation ``` --- ## Available Agents | Agent | Expertise | Trigger Phrases | |-------|-----------|-----------------| | `orchestrator` | Coordination | "comprehensive", "multi-perspective" | | `security-auditor` | Security | "security", "auth", "vulnerabilities" | | `penetration-tester` | Security Testing | "pentest", "red team", "exploit" | | `backend-specialist` | Backend | "API", "server", "Node.js", "Express" | | `frontend-specialist` | Frontend | "React", "UI", "components", "Next.js" | | `test-engineer` | Testing | "tests", "coverage", "TDD" | | `devops-engineer` | DevOps | "deploy", "CI/CD", "infrastructure" | | `database-architect` | Database | "schema", "Prisma", "migrations" | | `mobile-developer` | Mobile | "React Native", "Flutter", "mobile" | | `api-designer` | API Design | "REST", "GraphQL", "OpenAPI" | | `debugger` | Debugging | "bug", "error", "not working" | | `explorer-agent` | Discovery | "explore", "map", "structure" | | `documentation-writer` | Documentation | "write docs", "create README", "generate API docs" | | `performance-optimizer` | Performance | "slow", "optimize", "profiling" | | `project-planner` | Planning | "plan", "roadmap", "milestones" | | `seo-specialist` | SEO | "SEO", "meta tags", "search ranking" | | `game-developer` | Game Development | "game", "Unity", "Godot", "Phaser" | --- ## Claude Code Built-in Agents These work alongside custom agents: | Agent | Model | Purpose | |-------|-------|---------| | **Explore** | Haiku | Fast read-only codebase search | | **Plan** | Sonnet | Research during plan mode | | **General-purpose** | Sonnet | Complex multi-step modifications | Use **Explore** for quick searches, **custom agents** for domain expertise. --- ## Synthesis Protocol After all agents complete, synthesize: ```markdown ## Orchestration Synthesis ### Task Summary [What was accomplished] ### Agent Contributions | Agent | Finding | |-------|---------| | security-auditor | Found X | | backend-specialist | Identified Y | ### Consolidated Recommendations 1. **Critical**: [Issue from Agent A] 2. **Important**: [Issue from Agent B] 3. **Nice-to-have**: [Enhancement from Agent C] ### Action Items - [ ] Fix critical security issue - [ ] Refactor API endpoint - [ ] Add missing tests ``` --- ## Best Practices 1. **Available agents** - 17 specialized agents can be orchestrated 2. **Logical order** - Discovery → Analysis → Implementation → Testing 3. **Share context** - Pass relevant findings to subsequent agents 4. **Single synthesis** - One unified report, not separate outputs 5. **Verify changes** - Always include test-engineer for code modifications --- ## Key Benefits - ✅ **Single session** - All agents share context - ✅ **AI-controlled** - Claude orchestrates autonomously - ✅ **Native integration** - Works with built-in Explore, Plan agents - ✅ **Resume support** - Can continue previous agent work - ✅ **Context passing** - Findings flow between agents
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