hypothesis-generation
Skill10 starsChanged 4 days agoMITView on GitHub
Generate and freeze engineering research hypotheses before testing. Use when the user asks to "formulate hypotheses", "what could explain this", "propose mechanisms", or needs structured hypothesis generation for an engineering observation. Produces dated evidence boundaries, rival hypotheses, and discriminating predictions. Do NOT use for final hypothesis selection or experimental design — this skill generates candidates only, never scores or selects.
23 other projects use a version of this.
Adopted by
Most recently taken up by
- delorenj/skillstheir own version, first seen Nov 8, 2026
- BrightGold70/skillstheir own version, first seen Nov 8, 2026
- pradyumnasagar/open-research-skillstheir own version, first seen Nov 8, 2026
- K-Dense-AI/claude-scientific-writertheir own version, first seen Nov 7, 2026
- MarieLynneBlock/arcanum-artifextheir own version, first seen Nov 1, 2026
- PracticalSwan/agent-skillstheir own version, first seen Nov 1, 2026
Used with
Projects with it also use paper-lookup and venue-templates.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
YuchengZhang256Skillpaper-lookup
Look up a specific paper or exact-known query across 10 academic databases via their REST APIs (PubMed, PMC, bioRxiv, medRxiv, arXiv, OpenAlex, Crossref, Semantic Scholar, CORE, Unpaywall). Trigger ONLY when the user supplies a precise identifier (DOI, PMID, PMCID, arXiv ID, exact title) OR explicitly names one of these databases. Use for: fetching metadata for one known paper, pulling an abstract or full text for a known article, checking open-access status, retrieving a citation count, listing an author's publications, fetching references or citing papers for one specific paper. Single-shot targeted queries only — do NOT trigger on broad topic discovery ("find papers about X"), systematic review workflows, or methodological overlap scanning; those are handled elsewhere.
Also in 3 projects that use this
ZanderRussSkillvenue-templates
Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). This skill should be used when preparing manuscripts for journal submission, conference papers, research posters, or grant proposals and need venue-specific formatting requirements and templates.
Also in 3 projects that use this
Other versions23 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 23
- K-Dense-AI/claude-scientific-writer★ 2.6ksame name
- wu-yc/LabClaw★ 1.1ksame name
- LeonChaoX/qinyan-academic-skills★ 910same name
- jaechang-hits/SciAgent-Skills★ 386same name
- qinyan-ai/qinyan-academic-skills★ 80same name
- Barrios88/barrios-skills★ 63same name
- PracticalSwan/agent-skills★ 22same name
- delorenj/skills★ 17same name
- pradyumnasagar/open-research-skills★ 8same name
- MarieLynneBlock/arcanum-artifex★ 4same name
13 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository28 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .github/copilot-instructions.mdCopilot instructions
- architecturalSkill
- artifact-readingSkill
- auditSkill
- civilSkill
- compareSkill
- design-alternativesSkill
- electricalSkill
- eli5Skill
- engineering-researchSkill
- evidence-rankingSkill
- fmea-brainstormSkill
- gap-analysisSkill
- habitSkill
- mechanicalSkill
- peer-reviewSkill
- proposalSkill
- research-to-postSkill
- reviewSkill
- scholarly-researchSkill
- simplified-technical-englishSkill
- softwareSkill
- standards-lookupSkill
- summarizeSkill
- verifierSkill
- vitruvius-helpSkill
- vitruviusSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 1 is distinctive, and 2 are very specific to this project.
0
Common
Most of the 23 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 26
Before searching, name the question, the artifact/scope (or say it is a literature review), the jurisdiction/edition, and the effort budget …
- Very specific: line 110
Write outputs/hypothesis/<slug>.provenance.md beside the record (sources consulted, accepted, and rejected.
- Very specific: line 116
Never fabricate evidence to support a hypothesis.
“Common” is measured: kept by at least 6 in 10 of the 23 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
<!-- VITRUVIUS-COMPILED-SKILL:BEGIN v1 sha256=a617c15afa89b437f63aaa4faef797b4a12ddcfd77b4f30fadfa32427112dd20 -->Hypothesis Generation
Generate evidence-bounded engineering hypotheses. This skill freezes the observation, frames the question, establishes evidence boundaries, generates rival candidates, and derives discriminating predictions. It never scores, ranks, or selects hypotheses — that is a human decision.
Input Gate
Before searching, name the question, the artifact/scope (or say it is a
literature review), the jurisdiction/edition, and the effort budget (user-set or
thorough). Ask ONE clarifying question if the ask is too vague, then proceed.
See references/input-gate.md.
Invocation
/hypothesis-generation <observation>Include: the observed phenomenon, context, and any relevant engineering domain (materials, structures, thermal, etc.).
Methodology
- Freeze the observation — write the exact observation before interpreting. Distinguish what was measured from what is inferred. Timestamp the observation date.
- Frame the research question — restate as a falsifiable engineering question. Identify the claim type: descriptive, associational, predictive, causal, or mechanistic.
- Establish evidence boundary — document: search date, databases consulted, query terms, inclusion/exclusion criteria, limitations. "Not located within documented search boundary" — never "no prior work exists".
- Generate rival hypotheses — produce 3-5 candidates from DIFFERENT explanatory classes (e.g., material defect, design error, environmental, manufacturing process, maintenance). Each must be falsifiable. No two hypotheses from the same class.
- Declare claim type and estimand — specify what would be measured, the expected direction/magnitude, and the population/context where it applies.
- Derive discriminating predictions — for each hypothesis, state: condition, observable, expected pattern, falsifier (what result would be incompatible), and rival contrast (how does this prediction differ from the others?).
- Prevent HARKing — timestamp the generation. Preserve this document as the pre-registration record. Any deviation in testing must be reported as a deviation, not hidden.
Output
Inline Summary (chat response)
- Observation (frozen, dated)
- Research question + claim type
- Evidence boundary (date, sources, queries, limitations)
- 3-5 rival hypotheses with class labels
- For each: discriminating prediction + falsifier
Full Record (saved to disk)
Save to outputs/hypothesis/<slug>.md:
# Hypothesis Generation: <observation>
## Observation (Frozen)
- **Date observed:** <date>
- **Phenomenon:** <exact description>
- **Distinguish:** measured vs inferred
- **Context:** <engineering domain, conditions>
## Research Question
- **Question:** <falsifiable formulation>
- **Claim type:** descriptive / associational / predictive / causal / mechanistic
## Evidence Boundary
- **Search date:** <date>
- **Databases:** <OpenAlex, arXiv, standards, etc.>
- **Query terms:** <exact queries>
- **Inclusion:** <criteria>
- **Exclusion:** <criteria>
- **Limitations:** <what was not searched>
## Rival Hypotheses
### H1: <name> (<explanatory class>)
- **Mechanism:** <how it would cause the observation>
- **Prediction:** <expected result under this hypothesis>
- **Falsifier:** <what result would rule this out>
- **Rival contrast:** <how this differs from H2, H3...>
(repeat for H2, H3...)
## Discriminating Tests
- **Test that separates H1 from H2:** <experiment or analysis>
- **Test that separates H1 from H3:** <experiment or analysis>
- ...
## Pre-registration Record
- **Generated:** <timestamp>
- **Status:** candidate (never scored/selected by tool)
- **Deviations:** none yetWrite outputs/hypothesis/<slug>.provenance.md beside the record (sources consulted, accepted, and rejected; verification status). Minimal shape: references/provenance-sidecar.md.
Scope and Boundaries
- This skill generates hypothesis candidates — it does NOT score, rank, or select. Status must remain
candidate. - Research-only, not for final engineering sign-off. Hypothesis selection requires human engineering judgment.
- Never fabricate evidence to support a hypothesis. If a hypothesis lacks evidence, mark it
unverified, notinferred. - Evidence quality: see
references/evidence-quality-tiers.md.
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