Scientific Thinking Biology

scientific-thinking-biology — Structured Scientific Reasoning for Biology & Life Science

[中文文档](README_CN.md)

A biology-specific adaptation of [scientific-thinking-general](https://github.com/Agents365-ai/scientific-thinking-skill), with domain-specific reasoning layers for molecular biology, genetics, genomics, cell biology, immunology, neuroscience, ecology, and all life science research.

What it does

• Anchors reasoning to the correct biological level (molecular → cellular → tissue → organism → evolutionary)
• Distinguishes marker from driver, correlation from causation, enrichment from mechanism
• Evaluates the experimental system: in vitro / in vivo / ex vivo / clinical relevance and limits
• Applies a biological evidence hierarchy (genetic perturbation > biochemical > pharmacological > correlative omics)
• Flags biology-specific confounders: redundancy, compensation, composition bias, model organism gaps, overexpression artifacts, batch effects
• Calibrates claim language to evidence strength using biology-appropriate language
• Defines interpretation boundaries: species scope, cell type scope, disease context
• Suggests the lowest-cost next experiment that would discriminate between explanations

Multi-Platform Support

Works with all major AI agents that support the [Agent Skills](https://agentskills.io) format:

Platform	Status	Details
Claude Code	✅ Full support	Native SKILL.md format
OpenClaw / ClawHub	✅ Full support	metadata.openclaw namespace
Hermes Agent	✅ Full support	metadata.hermes namespace, category: research
Pi-Mo	✅ Full support	metadata.pimo namespace
SkillsMP	✅ Indexed	GitHub topics configured

Comparison: with vs. without this skill

Capability	Native agent	This skill
Distinguish marker from driver	No	Yes — requires functional perturbation
Evaluate experimental syste