hypothesis-generation

Name: hypothesis-generation
Author: K-Dense-AI

31kstars3.1kforks

How to install hypothesis-generation?

k-dense-ai/scientific-agent-skills/hypothesis-generation

$npx -y skills add K-Dense-AI/scientific-agent-skills --skill hypothesis-generation

Installs into the current project.

Summary

Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideati

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View on GitHub

SKILL.md

1	# Scientific Hypothesis Generation
2
3	## Overview
4
5	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.
6
7	## When to Use This Skill
8
9	This skill should be used when:
10	- Developing hypotheses from observations or preliminary data
11	- Designing experiments to test scientific questions
12	- Exploring competing explanations for phenomena
13	- Formulating testable predictions for research
14	- Conducting literature-based hypothesis generation
15	- Planning mechanistic studies across scientific domains
16
17	## Visual Enhancement with Scientific Schematics
18
19	⚠️ MANDATORY: Every hypothesis generation report MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.
20
21	This is not optional. Hypothesis reports without visual elements are incomplete. Before finalizing any document:
22	1. Generate at minimum ONE schematic or diagram (e.g., hypothesis framework showing competing explanations)
23	2. Prefer 2-3 figures for comprehensive reports (mechanistic pathway, experimental design flowchart, prediction decision tree)
24
25	How to generate figures:
26	- Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
27	- Simply describe your desired diagram in natural language
28	- Nano Banana Pro will automatically generate, review, and refine the schematic
29
30	How to generate schematics:
31	```bash
32	python scripts/generate_schematic.py "your diagram description" -o figures/output.png
33	```
34
35	The AI will automatically:
36	- Create publication-quality images with proper formatting
37	- Review and refine through multiple iterations
38	- Ensure accessibility (colorblind-friendly, high contrast)
39	- Save outputs in the figures/ directory
40
41	When to add schematics:
42	- Hypothesis framework diagrams showing competing explanations
43	- Experimental design flowcharts
44	- Mechanistic pathway diagrams
45	- Prediction decision trees
46	- Causal relationship diagrams
47	- Theoretical model visualizations
48	- Any complex concept that benefits from visualization
49
50	For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
51
52	---
53
54	## Workflow
55
56	Follow this systematic process to generate robust scientific hypotheses:
57
58	### 1. Understand the Phenomenon
59
60	Start by clarifying the observation, question, or phenomenon that requires explanation:
61
62	- Identify the core observation or pattern that needs explanation
63	- Define the scope and boundaries of the phenomenon
64	- Note any constraints or specific contexts
65	- Clarify what is already known vs. what is uncertain
66	- Identify the relevant scientific domain(s)
67
68	### 2. Conduct Comprehensive Literature Search
69
70	Search existing scientific literature to ground hypotheses in current evidence. Use both PubMed (for biomedical topics) and general web search (for broader scientific domains):
71
72	For biomedical topics:
73	- Use WebFetch with PubMed URLs to access relevant literature
74	- Search for recent reviews, meta-analyses, and primary research
75	- Look for similar phenomena, related mechanisms, or analogous systems
76
77	For all scientific domains:
78	- Use WebSearch to find recent papers, preprints, and reviews
79	- Search for established theories, mechanisms, or frameworks
80	- Identify gaps in current understanding
81
82	Search strategy:
83	- Begin with broad searches to understand the landscape
84	- Narrow to specific mechanisms, pathways, or theories
85	- Look for contradictory findings or unresolved debates
86	- Consult `references/literature_search_strategies.md` for detailed search techniques
87
88	### 3. Synthesize Existing Evidence
89
90	Analyze and integrate findings from literature search:
91
92	- Summarize current understanding of the phenomenon
93	- Identify established mechanisms or theories that may apply
94	- Note conflicting evidence or alternative viewpoints
95	- Recognize gaps, limitations, or unanswered questions
96	- Identify analogies from related systems or domains
97
98	### 4. Generate Competing Hypotheses
99
100	Devel

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hypothesis-generation

31kstars3.1kforks

View on GitHub

How to install hypothesis-generation?

k-dense-ai/scientific-agent-skills/hypothesis-generation

$npx -y skills add K-Dense-AI/scientific-agent-skills --skill hypothesis-generation

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Scientific Hypothesis Generation
2
3	## Overview
4
5	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.
6
7	## When to Use This Skill
8
9	This skill should be used when:
10	- Developing hypotheses from observations or preliminary data
11	- Designing experiments to test scientific questions
12	- Exploring competing explanations for phenomena
13	- Formulating testable predictions for research
14	- Conducting literature-based hypothesis generation
15	- Planning mechanistic studies across scientific domains
16
17	## Visual Enhancement with Scientific Schematics
18
19	⚠️ MANDATORY: Every hypothesis generation report MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.
20
21	This is not optional. Hypothesis reports without visual elements are incomplete. Before finalizing any document:
22	1. Generate at minimum ONE schematic or diagram (e.g., hypothesis framework showing competing explanations)
23	2. Prefer 2-3 figures for comprehensive reports (mechanistic pathway, experimental design flowchart, prediction decision tree)
24
25	How to generate figures:
26	- Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
27	- Simply describe your desired diagram in natural language
28	- Nano Banana Pro will automatically generate, review, and refine the schematic
29
30	How to generate schematics:
31	```bash
32	python scripts/generate_schematic.py "your diagram description" -o figures/output.png
33	```
34
35	The AI will automatically:
36	- Create publication-quality images with proper formatting
37	- Review and refine through multiple iterations
38	- Ensure accessibility (colorblind-friendly, high contrast)
39	- Save outputs in the figures/ directory
40
41	When to add schematics:
42	- Hypothesis framework diagrams showing competing explanations
43	- Experimental design flowcharts
44	- Mechanistic pathway diagrams
45	- Prediction decision trees
46	- Causal relationship diagrams
47	- Theoretical model visualizations
48	- Any complex concept that benefits from visualization
49
50	For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
51
52	---
53
54	## Workflow
55
56	Follow this systematic process to generate robust scientific hypotheses:
57
58	### 1. Understand the Phenomenon
59
60	Start by clarifying the observation, question, or phenomenon that requires explanation:
61
62	- Identify the core observation or pattern that needs explanation
63	- Define the scope and boundaries of the phenomenon
64	- Note any constraints or specific contexts
65	- Clarify what is already known vs. what is uncertain
66	- Identify the relevant scientific domain(s)
67
68	### 2. Conduct Comprehensive Literature Search
69
70	Search existing scientific literature to ground hypotheses in current evidence. Use both PubMed (for biomedical topics) and general web search (for broader scientific domains):
71
72	For biomedical topics:
73	- Use WebFetch with PubMed URLs to access relevant literature
74	- Search for recent reviews, meta-analyses, and primary research
75	- Look for similar phenomena, related mechanisms, or analogous systems
76
77	For all scientific domains:
78	- Use WebSearch to find recent papers, preprints, and reviews
79	- Search for established theories, mechanisms, or frameworks
80	- Identify gaps in current understanding
81
82	Search strategy:
83	- Begin with broad searches to understand the landscape
84	- Narrow to specific mechanisms, pathways, or theories
85	- Look for contradictory findings or unresolved debates
86	- Consult `references/literature_search_strategies.md` for detailed search techniques
87
88	### 3. Synthesize Existing Evidence
89
90	Analyze and integrate findings from literature search:
91
92	- Summarize current understanding of the phenomenon
93	- Identify established mechanisms or theories that may apply
94	- Note conflicting evidence or alternative viewpoints
95	- Recognize gaps, limitations, or unanswered questions
96	- Identify analogies from related systems or domains
97
98	### 4. Generate Competing Hypotheses
99
100	Devel

People who liked this also viewed

6 picks

Type