agent-coordination
Coordinate multiple agents for software development across any language. Use for parallel execution of independent tasks, sequential chains with dependencies, swarm analysis from multiple perspectives, or iterative refinement loops. Handles Python, JavaScript, Java, Go, Rust, C#, and other languages.
$ Installer
git clone https://github.com/d-o-hub/github-template-ai-agents /tmp/github-template-ai-agents && cp -r /tmp/github-template-ai-agents/.claude/skills/agent-coordination ~/.claude/skills/github-template-ai-agents// tip: Run this command in your terminal to install the skill
name: agent-coordination description: Coordinate multiple agents for software development across any language. Use for parallel execution of independent tasks, sequential chains with dependencies, swarm analysis from multiple perspectives, or iterative refinement loops. Handles Python, JavaScript, Java, Go, Rust, C#, and other languages.
Agent Coordination
Coordinate multiple agents efficiently for complex development tasks across any programming language.
Quick Start
Choose your coordination strategy:
Parallel - Independent tasks → See PARALLEL.md
Sequential - Dependent tasks → See SEQUENTIAL.md
Swarm - Multi-perspective analysis → See SWARM.md
Hybrid - Multi-phase workflows → See HYBRID.md
Iterative - Progressive refinement → See ITERATIVE.md
Available Agents
| Agent | Best For |
|---|---|
| code-reviewer | Quality assessment, standards |
| test-runner | Execute tests, verify functionality |
| feature-implementer | Build new capabilities |
| refactorer | Improve existing code |
| debugger | Diagnose and fix issues |
| security-auditor | Find vulnerabilities |
| performance-optimizer | Speed and efficiency |
| loop-agent | Orchestrate iterations |
Basic Workflow
- Choose strategy based on task structure
- Select agents matching required capabilities
- Execute with quality gates between phases
- Validate outputs before proceeding
- Synthesize results
Language Support
This coordination skill works with:
- Python (Django, Flask, FastAPI)
- JavaScript/TypeScript (Node.js, React, Vue)
- Java (Spring, Jakarta EE)
- Go (Gin, Echo)
- Rust (Actix, Rocket)
- C# (.NET, ASP.NET Core)
Common Patterns
Analysis + Execution:
1. Swarm analysis (parallel agents gather insights)
2. Sequential execution (apply findings)
3. Parallel validation (verify results)
Test-Driven Workflow:
1. test-runner: Run existing tests
2. feature-implementer: Add functionality
3. test-runner: Verify implementation
4. code-reviewer: Quality check
Performance Optimization:
Loop with performance-optimizer until:
- Metrics meet targets
- No more optimizations found
- Max iterations reached
Quality Gates
Between each phase, verify:
- Code compiles/parses correctly
- Tests pass with adequate coverage
- Security scans clean
- Performance acceptable
- No regressions introduced
Next Steps
Read the specific coordination pattern that matches your task structure. Each pattern includes detailed workflows, examples, and quality criteria.
Repository
