What problem does it solve?
This Skill automates the entire scientific-method research lifecycle to convert rough questions into refined problem statements, testable hypotheses, literature-backed assessments, executed experiments, and final findings and abstracts without ongoing operator intervention.
Core Features & Use Cases
- End-to-end orchestration: Refines problems, generates hypotheses, performs parallel literature reviews, designs and runs experiments, and writes findings.md and article-abstract.md.
- Resumable and idempotent: Detects progress from hypothesis and problem files and resumes interrupted runs without duplicating work.
- Parallel, agent-driven research: Spawns literature and experiment Tasks in parallel to accelerate slow research steps and maintain reproducible experiment artifacts.
- Use Case: Methodically investigate an open-ended scientific or debugging question (e.g., literature review + targeted experiments) to produce a publishable summary.
Quick Start
Invoke the researching skill with a problem slug and an initial description, for example: run researching on problem slug dark-matter with initial description "What accounts for missing mass in galaxy rotation?"