multi-agent-orchestration

Orchestrate complex tasks by spawning specialized sub-agents that run in parallel or sequential flows. Each agent handles an independent subtask with explicit input/output contracts and file-based communication, enabling decomposition of data pipelines, code analysis workflows, and multi-stage processing without blocking on dependencies.

Use multi-agent orchestration when tasks have clear independent subtasks, require specialized approaches for different components, benefit from parallel processing, or need fault isolation. It's ideal for data migrations, code analysis across multiple files, content creation pipelines, and multi-source data aggregation where one failure shouldn't halt the entire process.

Agents communicate through files rather than direct function calls, reducing context per agent and enabling graceful failure isolation. Each agent reads input from designated files, performs its task, and writes output to files that downstream agents consume, allowing independent operation and recovery without shared state.

Yes, spawn multiple specialized sub-agents for parallel execution with built-in progress tracking and fault isolation. Each agent runs independently with minimal context and explicit contracts, so you can monitor completion status and handle failures in individual agents without affecting parallel siblings.

Failures are isolated per agent through explicit input/output contracts and file-based communication. If one agent fails, others continue running independently, and you can retry or reassign that specific subtask without restarting the entire pipeline or losing progress from completed agents.

Yes, it's designed for data pipelines, code analysis workflows, content creation pipelines, and multi-source data aggregation. Decompose the workflow into parallel stages—fetch from multiple sources, process independently, aggregate results—with each agent handling its subtask and communicating via files.