Parallel Orchestration
Coordinate multiple specialized agents across parallel work streams with quality gates and conflict resolution.
Best use case
Parallel Orchestration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Coordinate multiple specialized agents across parallel work streams with quality gates and conflict resolution.
Teams using Parallel Orchestration 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-orchestration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Parallel Orchestration Compares
| Feature / Agent | Parallel Orchestration | 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?
Coordinate multiple specialized agents across parallel work streams with quality gates and conflict resolution.
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
# Parallel Orchestration Coordinate multiple specialized agents across parallel work streams with quality gates and conflict resolution. ## Agents - Database Engineer - `database-engineer` - API Developer - `api-developer` - UI Developer - `ui-developer` - Test Engineer - `test-engineer` - Documentation Writer - `documentation-writer` ## Workflow 1. Prepare execution plan with stream batches 2. Dispatch specialized agents per stream (ctx.parallel.all) 3. Execute tasks sequentially within each stream 4. Quality gate after each task with convergence loop (max 3 iterations) 5. Check for cross-stream conflicts 6. Resolve conflicts if found 7. Run integration verification 8. Merge stream results ## Inputs - `tasks` - Tasks from decomposition phase - `streams` - Work stream definitions - `qualityThreshold` - Minimum quality score (default: 80) - `maxParallel` - Maximum parallel streams (default: 5) - `githubRepo` - GitHub repo for progress sync (optional) ## Outputs - Per-stream execution results - Integration verification report - Conflict detection and resolution report - Merge result ## Agent Dispatch (5-12 parallel agents per issue) Agents are dispatched based on stream type: - `database` -> `database-engineer` - `api` -> `api-developer` - `ui` -> `ui-developer` - `testing` -> `test-engineer` - `docs` -> `documentation-writer` - `infrastructure` -> `architect` ## Process Files - `ccpm-parallel-execution.js` - Standalone parallel execution - `ccpm-orchestrator.js` - Phase 5 of full lifecycle
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