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MrGKanev

hypothesis-dev

by MrGKanev

Combination of Agent Skills for better workflows.

0🍴 0📅 Jan 21, 2026

SKILL.md


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

Score

Total Score

65/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

0/10
人気

GitHub Stars 100以上

0/15
最近の活動

1ヶ月以内に更新

+10
フォーク

10回以上フォークされている

0/5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

+5

Reviews

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