mapreduce

What problem does it solve?

MapReduce orchestrates parallel task execution by distributing work across multiple providers or agents and consolidating their outputs into a single, coherent result. This approach reduces bias, increases coverage, and accelerates complex workflows that benefit from diverse perspectives.

Core Features & Use Cases

• Parallel Task Distribution: Dispatch tasks to multiple workers (e.g., Claude, Codex, Gemini) to generate diverse outputs.
• Deterministic Reduction: Apply consolidation logic (reducers, rubrics, attribution) to produce a single trusted result.
• Use Case: Ideal for multi-provider planning, code generation, debugging, and decision synthesis where competing approaches improve quality and resilience.

Quick Start

Use the mapreduce skill to launch a parallel planning task, collect outputs, and consolidate them into specs/ROADMAP.md.