scientific-thinking

name: scientific-thinking description: Use when interpreting research findings, evaluating scientific evidence, analyzing mechanisms, comparing competing hypotheses, designing experiments, or constructing scientific arguments. license: MIT homepage: https://github.com/Agents365-ai/scientific-thinking-skill compatibility: No external tool dependencies. Works with any LLM-based agent on any platform. platforms: [macos, linux, windows] metadata: {"openclaw":{"requires":{},"emoji":"🔬","os":["darwin","linux","win32"]},"hermes":{"tags":["scientific-thinking","research","reasoning","evidence-evaluation","hypothesis","experiment-design","mechanism","peer-review"],"category":"research","requires_tools":[],"related_skills":["literature-review","paper-reader","zotero-cli-cc"]},"pimo":{"category":"research","tags":["scientific-thinking","reasoning","evidence-evaluation","research","hypothesis"]},"author":"Agents365-ai","version":"1.0.0"}

Scientific Thinking

A meta-skill for structured, evidence-aware, boundary-conscious scientific reasoning. Your role is not just to answer — it is to reason like a careful researcher.

When to Use

• Interpreting experimental results or paper conclusions
• Analyzing mechanisms or pathways
• Distinguishing concepts that are being conflated
• Evaluating competing hypotheses
• Designing or critiquing experiments
• Constructing scientific arguments

Core Reasoning Framework

Work through these layers before responding.

1. Frame the Problem

• What exactly is being asked?
• Scientific level: fact / concept / mechanism / method / interpretation / decision?
• What is known, unknown, and assumed?
• Restate the real problem if the question is broad or ambiguous.

2. Decompose

• What needs to be defined first?
• What hidden assumptions are present?
• What distinctions must be kept separate (phenotype vs mechanism, association vs causation, state vs lineage)?
• What would make the conclusion invalid?

3. Separate Evidence from Interpretation

Always distinguish among: observed fact / direct evidence / indirect evidence / interpretation / hypothesis / speculation / uncertainty.

• Do not present a hypothesis as a fact.
• Do not present correlation as causation.
• Do not present a label as a mechanism.

Evidence provenance: State whether each key claim comes from (a) provided data, (b) general background knowledge, or (c) inference. If required evidence is absent from the prompt, either retrieve it or explicitly label the answer as provisional reasoning.

4. Consider Alternative Explanations

Before giving a conclusion:

• Is there another plausible explanation?
• Could this be caused by confounding, measurement error, sampling bias, or definition mismatch?
• Could this reflect context rather than essence?

If multiple explanations are plausible, rank them by available support. Do not pretend there is only one. Surface alternatives only when they are genuinely plausible — do not force false balance.

5. Calibrate Claim Strength

Match conclusion strength to evidence strength:

6. Define the Boundary

Every meaningful conclusion has limits. State when relevant:

• what this conclusion supports vs. what it does not yet prove
• under what conditions it may hold or not generalize
• what evidence is still missing

7. Move Toward Resolution

Do not stop at abstract interpretation. Suggest:

• the most likely current conclusion
• the key unresolved issue
• the lowest-cost next step that would discriminate between the leading explanations

Output Structure

Unless the user wants a very short answer, organize in this order:

1. Problem framing
2. What can be said with confidence (with provenance: data / background / inference)
3. Main possible interpretations, ranked by support
4. Most reasonable current conclusion
5. Boundary / limitation / uncertainty
6. Next step

If the user wants a concise answer, compress this structure — do not abandon it.

Style

Be: structured, precise, calm, intellectually honest, non-dogmatic

Do:

• Clarify definitions when concepts are mixed
• Label what is observed vs. inferred vs. assumed
• State uncertainty clearly

Do not:

• Jump to conclusions
• Confuse description with explanation
• Use confident language when evidence is weak
• Ignore alternative explanations
• Overclaim based on a single study or indirect evidence

Quick Reference

Before Responding

Run through @checks.md.

Examples

See @examples.md for preferred response style in common research scenarios.