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. Also owns explicit HypoGeniC-style or automated LLM-driven hypothesis generation/testing requests inside this single skill. For open-ended ideation use scientific-brainstorming.
npx skills add https://github.com/foryourhealth111-pixel/Vibe-Skills --skill hypothesis-generation
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.
This skill should be used when:
Produce a structured hypothesis report when useful:
Figures or diagrams may be included when they clarify the hypothesis structure, but this skill does not require a second skill or helper expert to create them.
Follow this systematic process to generate robust scientific hypotheses:
Start by clarifying the observation, question, or phenomenon that requires explanation:
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:
For all scientific domains:
Search strategy:
references/literature_search_strategies.md for detailed search techniquesAnalyze and integrate findings from literature search:
Develop 3-5 distinct hypotheses that could explain the phenomenon. Each hypothesis should:
Strategies for generating hypotheses:
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.
For each viable hypothesis, propose specific experiments or studies to test it. Consult references/experimental_design_patterns.md for common approaches:
Experimental design elements:
Consider multiple approaches:
For each hypothesis, generate specific, quantitative predictions:
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):
\newpage before each hypothesis box to prevent content overflowKeep main text highly concise - only the most essential information. All details go to appendices.
Page Break Strategy:
\newpage before hypothesis boxes to ensure they start on fresh pagesAppendices (Comprehensive, Detailed):
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):
All detailed explanations, additional evidence, and comprehensive discussions belong in the appendices.
Critical Overflow Prevention:
\newpage before each hypothesis box to start it on a fresh pageCitation Requirements:
Aim for extensive citation to support all claims:
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:
\newpage before boxes that contain substantial content: \newpage
\begin{hypothesisbox1}[Hypothesis 1: Title]
% Long content here
\end{hypothesisbox1}
\newpage to start the box on a fresh page.\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.
Ensure all generated hypotheses meet these standards:
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 sourceshypothesis_generation.sty - LaTeX style package providing colored boxes, professional formatting, and custom environments for hypothesis reportshypothesis_report_template.tex - Complete LaTeX template with main text structure and comprehensive appendix sectionsFORMATTING_GUIDE.md - Quick reference guide with examples of all box types, color schemes, citation practices, and troubleshooting tipsUse this skill when implementing tasks according to Conductor's TDD workflow, handling phase checkpoints, managing git commits for tasks, or understanding the verification protocol.
Prepares and structurally reviews readiness evidence for ISO management-system and laboratory-competence standards - ISO 13485 medical device QMS, ISO 14971 device risk management, ISO/IEC 17025 testing and calibration laboratories, and ISO 15189 medical laboratories. Use when organizing declared scope, controlled documents, risk-management files, scope of accreditation, traceability, CAPA, external-provider controls, or bounded local evidence manifests, and when separating ISO certification from laboratory accreditation, FDA QMSR inspection, CLIA certification, MDSAP, and EU MDR/IVDR evidence boundaries. Not for legal applicability, compliance, certification, or accreditation decisions; contains no clause text.
Sample-size and statistical power calculations for planning studies. Use whenever someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for designs with no formula — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Use this skill even when the request only mentions an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-analysis.
Universal QA checklist for generated scientific plots: overlapping labels, clipped text, missing axes/legends, overcrowded data, and cross-journal resolution/format guidance.
Senior Elite Software Engineer (15+) and Senior Product Designer. Full workflow with planning, architecture, TDD, clean code, and pixel-perfect UX validation.
Run PinchBench benchmarks to evaluate OpenClaw agent performance across real-world tasks. Use when testing model capabilities, comparing models, submitting benchmark results to the leaderboard, or checking how well your OpenClaw setup handles calendar, email, research, coding, and multi-step workflows.
Use this skill when implementing tasks according to Conductor's TDD workflow, handling phase checkpoints, managing git commits for tasks, or understanding the verification protocol.
Verify PowerToys behavior end-to-end with the winapp CLI across two scenarios: (A) a module's release checklist against the installed build; (B) PR validation — derive each PR's checklist from its description + diff, then drive it against the installed build (a merged/shipped PR, or a whole release/hotfix set) or by building + sideloading the module when the PR isn't in the build yet (unmerged or not-yet-released). Drive each item via UIA invoke / Named Events / settings.json edits / clipboard / GPO / SendInput, and emit a structured PASS / FAIL / BLOCKED verdict per item with evidence (FAIL distinguishes product defects from stale/ambiguous checklist items). Use when asked to verify a module checklist, validate a PR, sign off a release/hotfix's PRs, or QA installed/sideloaded PowerToys bits. Combines generic winapp ui mechanics (references/winapp-ui-testing.md) with PT-specific recipes, per-scenario playbooks (references/scenarios/), and the helper .ps1 files shipped with this skill.
Take foryourhealth111-pixel/hypothesis-generation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.