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hypothesis-generation

8.1

by davila7

125Favorites
314Upvotes
0Downvotes

Generate testable hypotheses. Formulate from observations, design experiments, explore competing explanations, develop predictions, propose mechanisms, for scientific inquiry across domains.

hypothesis testing

8.1

Rating

0

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Data & Analytics

Category

Quick Review

Excellent skill for scientific hypothesis generation with comprehensive workflow coverage. The description clearly articulates when and how to use the skill for generating testable hypotheses across scientific domains. Task knowledge is extensive, providing an 8-step systematic process from literature review through experimental design, with strong emphasis on evidence-based mechanistic explanations and quality criteria. The structure is well-organized with clear workflow steps and appropriate delegation of detailed guidance to reference files. Professional LaTeX output with colored boxes and mandatory visual schematics adds significant value. The novelty score reflects that while hypothesis generation is achievable by LLMs, this skill's structured approach, quality frameworks, literature integration strategies, and formatted output templates meaningfully reduce token costs and improve consistency for complex scientific reasoning tasks. Minor areas for enhancement: could specify more concrete examples of domain-specific applications and provide clearer guidance on when simpler approaches might suffice versus when this comprehensive framework is warranted.

LLM Signals

Description coverage9
Task knowledge9
Structure8
Novelty7

GitHub Signals

18,073
1,635
132
71
Last commit 0 days ago

Publisher

davila7

davila7

Skill Author

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davila7

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