research

Coordinate autonomous agents to generate, debate, and evolve research hypotheses.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/achousal/EngramR --skill research-achousal
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: research
Source: https://github.com/achousal/EngramR/tree/main/.claude/skills/research
Command: npx skills add https://github.com/achousal/EngramR --skill research-achousal

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates the co-scientist generate-debate-evolve loop by defining research goals and coordinating participating skills to advance from idea to evaluated hypotheses, with provenance and structured feedback.

Core Features & Use Cases

  • Orchestrated loop: coordinates generate, review, tournament, meta-review, and evolve steps across multiple sub-skills.
  • Leadership and scoring: maintains an Elo-based leaderboard for hypotheses, driving objective evaluation and selection.
  • Knowledge governance: saves goals, meta-reviews, and landscape outputs to enable reproducible research cycles.

Quick Start

Define a research goal, then invoke the supervisor loop to generate, review, debate, and evolve hypotheses.

Frequently Asked Questions about research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate hypothesis generation and debate for research workflows?

Automate hypothesis generation and debate by orchestrating an autonomous agent loop that generates, reviews, and evolves research hypotheses based on a defined research goal.

What is the Elo ranking system used for in research hypothesis evaluation?

The Elo ranking system maintains a leaderboard that scores and objectively evaluates competing research hypotheses to drive iterative selection and refinement.

How do I start a co-scientist loop to evolve research hypotheses?

Start a co-scientist loop by defining structured research goal notes, then invoke the supervisor to coordinate generation, tournament, meta-review, and evolution steps.

Can I use autonomous agents to manage goal-definition and iterative research refinement?

Yes, autonomous agents coordinate goal-definition and iterative refinement by running generate-debate-evolve cycles and saving structured feedback for reproducible research.

What structured inputs are needed to run a generate-debate-evolve research workflow?

Running a generate-debate-evolve research workflow requires structured goal notes and hypothesis notes to properly coordinate the participating sub-skills and meta-reviews.

Does the research workflow Skill require external dependencies to coordinate meta-reviews?

No, the research workflow Skill has no external dependencies, but it does require access to internal sub-skills to successfully execute generation, tournament, and evolve steps.