hypothesis-dev

name	hypothesis-dev
description	Develop testable scientific hypotheses through systematic observation analysis, literature grounding, and rigorous experimental design. Guides the journey from observation to testable prediction.
allowed-tools	["Read","Write","Edit","Bash","WebSearch","WebFetch","Task"]

Hypothesis Development Assistant

Purpose

Transform observations and research questions into well-formed, testable hypotheses grounded in existing evidence. This skill guides systematic hypothesis generation across scientific disciplines.

Development Workflow

Step 1: Define the Phenomenon

• Articulate the observation or question clearly
• Identify what is known versus unknown
• Establish the knowledge gap to address

Step 2: Ground in Literature

• Search existing research using paper-search and lit-review skills
• Identify relevant theories and prior findings
• Note contradictions or unexplained patterns

Step 3: Synthesize Evidence

• Integrate findings across sources
• Map the current state of knowledge
• Pinpoint specific gaps your hypothesis could address

Step 4: Generate Competing Explanations

• Develop 3-5 distinct mechanistic hypotheses
• Ensure each offers a different explanation
• Consider null and alternative framings

Step 5: Evaluate Hypothesis Quality

Assess each hypothesis against criteria:

• Testability: Can it be empirically examined?
• Falsifiability: What would disprove it?
• Explanatory scope: How much does it explain?
• Parsimony: Is it appropriately simple?
• Consistency: Does it align with established knowledge?

Step 6: Design Experimental Tests

• Propose specific experiments for each hypothesis
• Identify required methods and resources
• Consider feasibility and ethical constraints

Step 7: Formulate Predictions

• Generate quantitative, testable predictions
• Specify expected outcomes under each hypothesis
• Define criteria for supporting or rejecting

Step 8: Document Systematically

• Structure output for clarity and rigor
• Include competing hypotheses with rationales
• Present experimental roadmap

Quality Standards

Strong hypotheses must be:

• Evidence-based: Grounded in prior research
• Testable: Amenable to empirical investigation
• Mechanistic: Explaining how/why, not just what
• Specific: Clear enough to guide experiments
• Falsifiable: Capable of being proven wrong

Output Structure

Executive Summary

Brief overview of the question and leading hypotheses

Competing Hypotheses Section

Present each hypothesis with:

• Clear statement
• Supporting evidence
• Mechanistic explanation
• Distinguishing predictions

Experimental Roadmap

• Prioritized tests
• Required resources
• Decision criteria

Literature Foundation

Comprehensive citations supporting the analysis (aim for 30-50+ sources for thorough work)

Integration

Works alongside:

• paper-search for literature discovery
• lit-review for evidence synthesis
• academic-writing for manuscript preparation