Skills hypothesis-generation
📦

hypothesis-generation

Content revision r1 Safe 🌐 Network access⚙️ External commands

Generate Testable Scientific Hypotheses

Researchers need to turn observations into clear, testable explanations. This skill structures evidence review, competing hypotheses, predictions, and experiment plans.

Supports: Claude Codex Code(CC)
🥈 80 Silver

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
Review the Skillstore skill "hypothesis-generation" from https://skillstore.io/skills/k-dense-ai-hypothesis-generation.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-hypothesis-generation/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/k-dense-ai-hypothesis-generation.md Signed manifest GET /api/skills/k-dense-ai-hypothesis-generation/manifest Signed lockfile GET /api/skills/k-dense-ai-hypothesis-generation/lockfile

Test it

Using "hypothesis-generation". Observation: Cell growth slows after treatment, but viability remains high.

Expected outcome:

  • Three competing mechanisms that explain slowed growth without cell death.
  • Predictions for cell-cycle markers, metabolic activity, and recovery after washout.
  • Two experiments with controls that separate cytostasis from delayed toxicity.

Using "hypothesis-generation". Observation: A biomarker rises before symptoms in a longitudinal cohort.

Expected outcome:

  • Causal, compensatory, and confounded association hypotheses.
  • Quality assessment across testability, parsimony, and explanatory power.
  • A study plan using time-lag analysis, matched controls, and validation cohorts.

Using "hypothesis-generation". Goal: Prepare a hypothesis report for a grant planning meeting.

Expected outcome:

  • Executive summary with prioritized hypotheses and key evidence.
  • Prediction matrix showing results that support or falsify each explanation.
  • Appendix outline for literature, protocols, assumptions, and limitations.

Security Audit

Safe
v7 • 7/6/2026 Open versioned report

Static reconnaissance and network findings are false positives from scientific prose and PubMed search templates. External-command detections are Markdown code fences or inline LaTeX and file references, with no evidence of hidden execution, credential access, or exfiltration. No prompt injection attempt or semantic abuse was found.

7
Files scanned
3,001
Lines analyzed
0
Review items
0
False positives ignored

Risk Factors

🌐 Network access (4)
references/literature_search_strategies.md:104 references/literature_search_strategies.md:109 references/literature_search_strategies.md:114 references/literature_search_strategies.md:119
⚙️ External commands (32)
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No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
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Open versioned report
Security Assessment

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Academic citations (APA · BibTeX · CFF)

APA citation

K-Dense-AI. (2026). hypothesis-generation security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-hypothesis-generation/audits/7

BibTeX citation

@techreport{k-dense-ai-k-dense-ai-hypothesis-generation-2026, author = {K-Dense-AI}, title = {hypothesis-generation security audit report (audit version 7)}, institution = {Skillstore}, year = {2026}, number = {7}, url = {https://skillstore.io/skills/k-dense-ai-hypothesis-generation/audits/7}, note = {Author version unspecified} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "hypothesis-generation security audit report (audit version 7)" version: "unspecified" type: report authors: - name: "K-Dense-AI" date-released: "2026-07-06" url: "https://skillstore.io/skills/k-dense-ai-hypothesis-generation/audits/7" identifiers: - type: other value: "skillstore:k-dense-ai-hypothesis-generation:audit:7" description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score
K-Dense-AI Recommended Current

k-dense-ai-hypothesis-generation

Skillstore Score 80
Evidence Confidence High
Skillstore usage 27
Updated

2026-09-09

davila7

davila7-hypothesis-generation

Skillstore Score 79
Evidence Confidence High
Skillstore usage 13
Updated

2026-09-09

Skillstore Score

Why this score Evidence Confidence: High
59
Architecture
85
Maintainability
87
Content
73
Community
91
Spec Compliance

What You Can Build

Plan a Thesis Project

Convert preliminary observations into competing hypotheses, measurable predictions, and experiments for a research proposal.

Explore Product Research Signals

Analyze unexpected experimental results and produce mechanistic explanations with tests for the next lab cycle.

Review Research Directions

Compare several scientific explanations and prioritize the studies most likely to distinguish them.

Try These Prompts

Generate Initial Hypotheses 
Use this observation: [observation]. Generate three testable hypotheses, key assumptions, and one prediction for each.
Compare Explanations 
Analyze these observations: [observations]. Create competing hypotheses, rank them by testability, and list evidence needed to distinguish them.
Plan Experiments 
For this hypothesis: [hypothesis]. Propose experiments, controls, measurements, confounds, and falsifying outcomes.
Build Research Report 
Develop a structured hypothesis report for [phenomenon]. Include literature search strategy, competing mechanisms, predictions, experimental designs, and appendix-ready evidence notes.

Best Practices

  • Provide the core observation, domain, existing data, and known constraints before starting.
  • Ask for competing hypotheses rather than a single preferred explanation.
  • Review proposed experiments with domain experts before using them in real studies.

Avoid

  • Using the skill to confirm a preferred hypothesis without testing alternatives.
  • Treating generated citations or mechanisms as verified without source review.
  • Skipping controls, confounds, and falsifying outcomes in experiment plans.

Frequently Asked Questions

What does this skill help produce?
It helps produce testable scientific hypotheses, predictions, experiment plans, and structured hypothesis reports.
Can it search the latest literature?
It can guide literature search and use available web tools when the environment provides them.
Does it replace a subject matter expert?
No. Expert review is still needed for feasibility, safety, ethics, and interpretation.
Which tools can use this skill?
The report lists support for Claude, Codex, and Claude Code.
What inputs improve results?
Provide observations, measurements, study context, constraints, and relevant papers or datasets.
Can it create publication-ready reports?
It can draft a structured LaTeX report, but final content and citations need review.

Developer Details

Author

K-Dense-AI

License

MIT license

Skillstore revision

r1

Version notice

The author did not declare a version.

Repository

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/hypothesis-generation

Ref

b8ca75d2c0a7e7102978993058777d82b8ab2610

Maintenance freshness

7/18/2026

Usage

11 downloads · 415 views

File structure

📁 assets/

📄 FORMATTING_GUIDE.md

📄 hypothesis_generation.sty

📄 hypothesis_report_template.tex

📁 references/

📄 experimental_design_patterns.md

📄 hypothesis_quality_criteria.md

📄 literature_search_strategies.md

📄 SKILL.md

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