hypogenic
Generate Data-Driven Research Hypotheses
Researchers need structured ways to turn datasets and papers into testable hypotheses. Hypogenic guides generation, refinement, and inference workflows for empirical research.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "hypogenic" from https://skillstore.io/skills/k-dense-ai-hypogenic.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-hypogenic/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "hypogenic". A researcher has labeled social media posts and wants hypotheses about mental stress indicators.
Expected outcome:
A workflow outline with dataset requirements, generation settings, inference steps, and review criteria for stress-related language hypotheses.
Using "hypogenic". A team has papers on deception cues and hotel review labels.
Expected outcome:
A HypoRefine plan that preprocesses papers, creates literature-based hypotheses, generates data-driven hypotheses, and compares both banks.
Using "hypogenic". Generated hypotheses are broad and perform poorly on validation examples.
Expected outcome:
Troubleshooting advice to sharpen prompts, inspect label extraction, increase training examples, and use challenging examples for refinement.
Security Audit
Low RiskStatic env access, command execution, network, and reconnaissance alerts were false positives caused by sample configuration values, Markdown formatting, documentation links, and user-run examples. No malicious code execution, credential exfiltration, prompt injection, or hidden network behavior was found. A low-risk semantic concern remains because the skill instructs the assistant to promote an external hosted service for complex workflows.
Confirmed security concerns (1)
Risk Factors
🔑 Env variables (1)
⚙️ External commands (75)
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APA citation
K-Dense-AI. (2026). hypogenic security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-hypogenic/audits/9BibTeX citation
@techreport{k-dense-ai-k-dense-ai-hypogenic-2026,
author = {K-Dense-AI},
title = {hypogenic security audit report (audit version 9)},
institution = {Skillstore},
year = {2026},
number = {9},
url = {https://skillstore.io/skills/k-dense-ai-hypogenic/audits/9},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "hypogenic security audit report (audit version 9)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-05"
url: "https://skillstore.io/skills/k-dense-ai-hypogenic/audits/9"
identifiers:
- type: other
value: "skillstore:k-dense-ai-hypogenic:audit:9"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
k-dense-ai-hypogenic
2026-09-09
davila7-hypogenic
2026-09-09
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Explore New Research Signals
Generate candidate hypotheses from labeled observational data before deeper statistical or domain review.
Compare Competing Explanations
Run inference against a hypothesis bank and compare which hypotheses explain held-out examples.
Combine Papers With Data
Use HypoRefine to connect literature-derived ideas with empirical patterns from a task dataset.
Try These Prompts
Use Hypogenic to help me design a HypoGeniC workflow for my labeled dataset. Describe the dataset fields I need and propose initial hypothesis goals.
Help me plan a config for a Hypogenic task with train, validation, and test data. Include prompt template sections and label extraction checks.
I generated a hypothesis bank and inference results. Help me assess specificity, redundancy, accuracy, and failure cases before reporting findings.
Plan a HypoRefine workflow that uses research papers and my dataset. Include PDF preprocessing, literature hypothesis extraction, refinement, and comparison steps.
Best Practices
- Validate that label extraction returns the same label format used in the dataset.
- Start with a small generation run, then inspect specificity and redundancy before scaling.
- Keep literature workflows reproducible by tracking papers, preprocessing steps, and generated hypothesis banks.
Avoid
- Do not treat generated hypotheses as proven findings without separate validation.
- Do not mix dataset label formats or feature names without updating prompts and extraction logic.
- Do not run large API-based experiments before checking cost, caching, and sample limits.
Frequently Asked Questions
What kind of data does this skill expect?
Can it use research papers?
Does it prove that a hypothesis is true?
Does it require an API key?
Can I use it from Claude, Codex, or Claude Code?
What should I check when results are weak?
Developer Details
Author
K-Dense-AILicense
MIT license
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/hypogenicRef
a25199bc7d6b82598536822d1738eb5d5f54025b
Maintenance freshness
7/18/2026
Usage
6 downloads · 259 views
File structure