Task Researcher

Example Use Cases

• 1

  Convert functional/technical spec files into structured project tasks and subtasks programmatically.

• 2

  Augment task expansion with live web research (knowledge-storm) to produce highly informed subtasks and research reports.

• 3

  Analyze task complexity, validate and fix dependencies, and generate per-task files for downstream processing or execution.

Description

Task Researcher provides a CLI and an MCP server to generate, expand, analyze, and manage project tasks using LLMs and the knowledge-storm engine. It can parse project spec files into initial tasks, break tasks into subtasks (optionally using automated STORM research to gather web evidence), analyze task complexity, validate and fix dependencies, and emit per-task files. The MCP server exposes tools and resources so agents (e.g., Claude Desktop) can call parse/update/expand/validate/research operations programmatically. This enables agents to combine AI-driven planning with automated external research to produce well-informed implementation tasks and reports.