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Agent Skill · 研究检索

hypothesis-generation(假设生成)

hypothesis-generation 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

hypothesis-generation 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 15,699。

总安装 7,662周安装 313GitHub Stars 26,425下载 2,454核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:hypothesis-generation(假设生成)
来源仓库:https://github.com/davila7/claude-code-templates
仓库路径:skills/hypothesis-generation
安装命令:
npx skills add https://github.com/davila7/claude-code-templates --skill hypothesis-generation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/davila7/claude-code-templates --skill hypothesis-generation

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

hypothesis-generation 提供系统化假设开发框架,支持从观察到可测试解释的转化。适用于科研探索、实验设计与竞争性理论评估等科学推理场景。引导用户基于证据提出假设、设计验证方案并生成预测性陈述。使用时需明确研究问题与观测基础,避免在无数据支撑下进行纯推测性推演。

输出建议应配合领域专家判断,不可替代严谨的实验验证流程。

来源仓库内路径:skills/hypothesis-generation

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/davila7/claude-code-templates --skill hypothes…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

hypothesis-generation 怎么安装?

在终端执行 npx skills add https://github.com/davila7/claude-code-templates --skill hypothesis-generat…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

hypothesis-generation 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

hypothesis-generation 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

hypothesis-generation 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

hypothesis-generation 用的人多吗?

公开数据是累计安装 7,662 次,近一周安装 313 次,下载 2,454 次,GitHub 26,425 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

hypothesis-generation 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 来源仓库有 26,425 星,维护活跃度相对可查。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
hypothesis-generation

假设生成 · 本页

7,66226,425需要联网MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Scientific Hypothesis Generation

Overview

Hypothesis generation is a systematic process for developing testable explanations. Formulate evidence-based hypotheses from observations, design experiments, explore competing explanations, and develop predictions. Apply this skill for scientific inquiry across domains.

When to Use This Skill

This skill should be used when:

  • Developing hypotheses from observations or preliminary data
  • Designing experiments to test scientific questions
  • Exploring competing explanations for phenomena
  • Formulating testable predictions for research
  • Conducting literature-based hypothesis generation
  • Planning mechanistic studies across scientific domains

Visual Enhancement with Scientific Schematics

⚠️ MANDATORY: Every hypothesis generation report MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.

This is not optional. Hypothesis reports without visual elements are incomplete. Before finalizing any document:

  1. Generate at minimum ONE schematic or diagram (e.g., hypothesis framework showing competing explanations)
  2. Prefer 2-3 figures for comprehensive reports (mechanistic pathway, experimental design flowchart, prediction decision tree)

How to generate figures:

  • Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
  • Simply describe your desired diagram in natural language
  • Nano Banana Pro will automatically generate, review, and refine the schematic

How to generate schematics:

python scripts/generate_schematic.py "your diagram description" -o figures/output.png

The AI will automatically:

  • Create publication-quality images with proper formatting
  • Review and refine through multiple iterations
  • Ensure accessibility (colorblind-friendly, high contrast)
  • Save outputs in the figures/ directory

When to add schematics:

  • Hypothesis framework diagrams showing competing explanations
  • Experimental design flowcharts
  • Mechanistic pathway diagrams
  • Prediction decision trees
  • Causal relationship diagrams
  • Theoretical model visualizations
  • Any complex concept that benefits from visualization

For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.


Workflow

Follow this systematic process to generate robust scientific hypotheses:

1. Understand the Phenomenon

Start by clarifying the observation, question, or phenomenon that requires explanation:

  • Identify the core observation or pattern that needs explanation
  • Define the scope and boundaries of the phenomenon
  • Note any constraints or specific contexts
  • Clarify what is already known vs. what is uncertain
  • Identify the relevant scientific domain(s)

2. Conduct Comprehensive Literature Search

Search existing scientific literature to ground hypotheses in current evidence. Use both PubMed (for biomedical topics) and general web search (for broader scientific domains):

For biomedical topics:

  • Use WebFetch with PubMed URLs to access relevant literature
  • Search for recent reviews, meta-analyses, and primary research
  • Look for similar phenomena, related mechanisms, or analogous systems

For all scientific domains:

  • Use WebSearch to find recent papers, preprints, and reviews
  • Search for established theories, mechanisms, or frameworks
  • Identify gaps in current understanding

Search strategy:

  • Begin with broad searches to understand the landscape
  • Narrow to specific mechanisms, pathways, or theories
  • Look for contradictory findings or unresolved debates
  • Consult references/literature_search_strategies.md for detailed search techniques

3. Synthesize Existing Evidence

Analyze and integrate findings from literature search:

  • Summarize current understanding of the phenomenon
  • Identify established mechanisms or theories that may apply
  • Note conflicting evidence or alternative viewpoints
  • Recognize gaps, limitations, or unanswered questions
  • Identify analogies from related systems or domains

4. Generate Competing Hypotheses

Develop 3-5 distinct hypotheses that could explain the phenomenon. Each hypothesis should:

  • Provide a mechanistic explanation (not just description)
  • Be distinguishable from other hypotheses
  • Draw on evidence from the literature synthesis
  • Consider different levels of explanation (molecular, cellular, systemic, population, etc.)

Strategies for generating hypotheses:

  • Apply known mechanisms from analogous systems
  • Consider multiple causative pathways
  • Explore different scales of explanation
  • Question assumptions in existing explanations
  • Combine mechanisms in novel ways

5. Evaluate Hypothesis Quality

Assess each hypothesis against established quality criteria from references/hypothesis_quality_criteria.md:

Testability: Can the hypothesis be empirically tested? Falsifiability: What observations would disprove it? Parsimony: Is it the simplest explanation that fits the evidence? Explanatory Power: How much of the phenomenon does it explain? Scope: What range of observations does it cover? Consistency: Does it align with established principles? Novelty: Does it offer new insights beyond existing explanations?

Explicitly note the strengths and weaknesses of each hypothesis.

6. Design Experimental Tests

For each viable hypothesis, propose specific experiments or studies to test it. Consult references/experimental_design_patterns.md for common approaches:

Experimental design elements:

  • What would be measured or observed?
  • What comparisons or controls are needed?
  • What methods or techniques would be used?
  • What sample sizes or statistical approaches are appropriate?
  • What are potential confounds and how to address them?

Consider multiple approaches:

  • Laboratory experiments (in vitro, in vivo, computational)
  • Observational studies (cross-sectional, longitudinal, case-control)
  • Clinical trials (if applicable)
  • Natural experiments or quasi-experimental designs

7. Formulate Testable Predictions

For each hypothesis, generate specific, quantitative predictions:

  • State what should be observed if the hypothesis is correct
  • Specify expected direction and magnitude of effects when possible
  • Identify conditions under which predictions should hold
  • Distinguish predictions between competing hypotheses
  • Note predictions that would falsify the hypothesis

8. Present Structured Output

Generate a professional LaTeX document using the template in assets/hypothesis_report_template.tex. The report should be well-formatted with colored boxes for visual organization and divided into a concise main text with comprehensive appendices.

Document Structure:

Main Text (Maximum 4 pages):

  1. Executive Summary - Brief overview in summary box (0.5-1 page)
  2. Competing Hypotheses - Each hypothesis in its own colored box with brief mechanistic explanation and key evidence (2-2.5 pages for 3-5 hypotheses)

- IMPORTANT: Use \newpage before each hypothesis box to prevent content overflow - Each box should be ≤0.6 pages maximum

  1. Testable Predictions - Key predictions in amber boxes (0.5-1 page)
  2. Critical Comparisons - Priority comparison boxes (0.5-1 page)

Keep main text highly concise - only the most essential information. All details go to appendices.

Page Break Strategy:

  • Always use \newpage before hypothesis boxes to ensure they start on fresh pages
  • This prevents content from overflowing off page boundaries
  • LaTeX boxes (tcolorbox) do not automatically break across pages

Appendices (Comprehensive, Detailed):

  • Appendix A: Comprehensive literature review with extensive citations
  • Appendix B: Detailed experimental designs with full protocols
  • Appendix C: Quality assessment tables and detailed evaluations
  • Appendix D: Supplementary evidence and analogous systems

Colored Box Usage:

Use the custom box environments from hypothesis_generation.sty:

  • hypothesisbox1 through hypothesisbox5 - For each competing hypothesis (blue, green, purple, teal, orange)
  • predictionbox - For testable predictions (amber)
  • comparisonbox - For critical comparisons (steel gray)
  • evidencebox - For supporting evidence highlights (light blue)
  • summarybox - For executive summary (blue)

Each hypothesis box should contain (keep concise for 4-page limit):

  • Mechanistic Explanation: 1-2 brief paragraphs (6-10 sentences max) explaining HOW and WHY
  • Key Supporting Evidence: 2-3 bullet points with citations (most important evidence only)
  • Core Assumptions: 1-2 critical assumptions

All detailed explanations, additional evidence, and comprehensive discussions belong in the appendices.

Critical Overflow Prevention:

  • Insert \newpage before each hypothesis box to start it on a fresh page
  • Keep each complete hypothesis box to ≤0.6 pages (approximately 15-20 lines of content)
  • If content exceeds this, move additional details to Appendix A
  • Never let boxes overflow off page boundaries - this creates unreadable PDFs

Citation Requirements:

Aim for extensive citation to support all claims:

  • Main text: 10-15 key citations for most important evidence only (keep concise for 4-page limit)
  • Appendix A: 40-70+ comprehensive citations covering all relevant literature
  • Total target: 50+ references in bibliography

Main text citations should be selective - cite only the most critical papers. All comprehensive citation and detailed literature discussion belongs in the appendices. Use \citep{author2023} for parenthetical citations.

LaTeX Compilation:

The template requires XeLaTeX or LuaLaTeX for proper rendering:

xelatex hypothesis_report.tex
bibtex hypothesis_report
xelatex hypothesis_report.tex
xelatex hypothesis_report.tex

Required packages: The hypothesis_generation.sty style package must be in the same directory or LaTeX path. It requires: tcolorbox, xcolor, fontspec, fancyhdr, titlesec, enumitem, booktabs, natbib.

Page Overflow Prevention:

To prevent content from overflowing on pages, follow these critical guidelines:

  1. Monitor Box Content Length: Each hypothesis box should fit comfortably on a single page. If content exceeds ~0.7 pages, it will likely overflow.
  2. Use Strategic Page Breaks: Insert \newpage before boxes that contain substantial content: \newpage \begin{hypothesisbox1}[Hypothesis 1: Title] % Long content here \end{hypothesisbox1}
  3. Keep Main Text Boxes Concise: For the 4-page main text limit:

- Each hypothesis box: Maximum 0.5-0.6 pages - Mechanistic explanation: 1-2 brief paragraphs only (6-10 sentences max) - Key evidence: 2-3 bullet points only - Core assumptions: 1-2 items only - If content is longer, move details to appendices

  1. Break Long Content: If a hypothesis requires extensive explanation, split across main text and appendix:

- Main text box: Brief mechanistic overview + 2-3 key evidence points - Appendix A: Detailed mechanism explanation, comprehensive evidence, extended discussion

  1. Test Page Boundaries: Before each new box, consider if remaining page space is sufficient. If less than 0.6 pages remain, use \newpage to start the box on a fresh page.
  2. Appendix Page Management: In appendices, use \newpage between major sections to avoid overflow in detailed content areas.

Quick Reference: See assets/FORMATTING_GUIDE.md for detailed examples of all box types, color schemes, and common formatting patterns.

Quality Standards

Ensure all generated hypotheses meet these standards:

  • Evidence-based: Grounded in existing literature with citations
  • Testable: Include specific, measurable predictions
  • Mechanistic: Explain how/why, not just what
  • Comprehensive: Consider alternative explanations
  • Rigorous: Include experimental designs to test predictions

Resources

references/

  • hypothesis_quality_criteria.md - Framework for evaluating hypothesis quality (testability, falsifiability, parsimony, explanatory power, scope, consistency)
  • experimental_design_patterns.md - Common experimental approaches across domains (RCTs, observational studies, lab experiments, computational models)
  • literature_search_strategies.md - Effective search techniques for PubMed and general scientific sources

assets/

  • hypothesis_generation.sty - LaTeX style package providing colored boxes, professional formatting, and custom environments for hypothesis reports
  • hypothesis_report_template.tex - Complete LaTeX template with main text structure and comprehensive appendix sections
  • FORMATTING_GUIDE.md - Quick reference guide with examples of all box types, color schemes, citation practices, and troubleshooting tips

平台分布

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28.27%
按下载量换算694

Cursor

23.29%
按下载量换算572

OpenCode

21.34%
按下载量换算524

Gemini CLI

12.35%
按下载量换算303

Antigravity

9.11%
按下载量换算224

Codex

3.4%
按下载量换算83

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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