What domains are best suited for Hypogenic?

It excels in empirical research tasks requiring pattern discovery, such as deception detection, AI content identification, and mental health indicator analysis.

Does it support local LLMs?

Yes, Hypogenic supports both API-based models (OpenAI, Anthropic) and local LLM deployments for privacy or cost management.

What is the HypoGeniC method within this skill?

It is a data-driven approach that generates scientific hypotheses solely from observational datasets through iterative refinement without requiring prior literature.

Can I use research papers with this skill?

Yes, the HypoRefine and Union methods integrate existing literature by processing PDFs via GROBID to extract and combine theoretical insights with data-driven patterns.

How does it help reduce API costs?

The framework includes a Redis caching layer that stores LLM responses, preventing redundant API calls during iterative generation and testing cycles.

Hypogenic Scientific Research

Name: Hypogenic Scientific Research
Author: Activer007

byActiver007

0•

Data Science & ML

Automates scientific hypothesis generation and testing by combining literature insights with empirical data patterns using large language models.

Hypogenic is a specialized framework designed to accelerate scientific discovery by automating the formulation and validation of research hypotheses. It enables researchers to generate data-driven hypotheses, integrate existing literature insights through PDF processing, and perform systematic testing against observational datasets. Whether you are investigating deception detection, AI-generated content, or mental health indicators, this skill provides a rigorous, LLM-powered pipeline to move from raw data to testable scientific insights with significantly improved accuracy and hypothesis diversity compared to manual baseline methods.

Key Features

01Automated data-driven hypothesis generation from observational datasets

02Agentic integration of research literature via PDF and GROBID processing

03Iterative hypothesis refinement based on performance and validation

04Multi-hypothesis inference for systematic empirical testing

05Redis-backed caching for cost-effective LLM experimentation

060 GitHub stars

Use Cases

01Developing theory-grounded markers for mental health analysis in social media

02Conducting exploratory research in deception detection using observational datasets

03Identifying behavioral patterns for AI-generated content detection

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add activer007/ordinary-claude-skills hypogenic

For use in Claude.ai and ChatGPT

Download Skill