hypothesis-generation
/hypothesis-generation
Generuje i zamraża inżynierskie hipotezy badawcze przed testowaniem, tworząc datowane granice dowodów, hipotezy konkurencyjne i przewidywania rozróżniające, bez ich oceniania i wyboru.
- Autor
- adeerkhan ↗
- Repozytorium
- vitruvius ↗
- Licencja
- MIT
- Ostatnia zmiana repozytorium
- 17.10.2026
Ocena i bezpieczeństwo
- Pliki w paczce
- 1
- Skrypty
- 0
- Komentarze HTML
- 1
- Adresy URL w SKILL.md
- 0
Brak sygnałów. Repozytorium zmienione 17.10.2026, bez odwołań do wycofanych modeli i API.
MIT, otwarta: można używać i zmieniać, z zachowaniem informacji o autorze.
- SKILL.md zawiera komentarze HTML (1). Nie widać ich w podglądzie Markdown, a model je czyta.
Co robi i kiedy
Generuje i zamraża inżynierskie hipotezy badawcze przed testowaniem, tworząc datowane granice dowodów, hipotezy konkurencyjne i przewidywania rozróżniające, bez ich oceniania i wyboru.
Wyzwalacze z opisu
Argumenty
/hypothesis-generation <engineering observation or phenomenon>
Oryginalny opis (EN)
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.
Jak działa
- Input Gate
- Invocation
- Methodology
- Output
- Scope and Boundaries
Podgląd SKILL.md
--- name: hypothesis-generation description: > 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. argument-hint: "<engineering observation or phenomenon>" allowed-tools: Write Edit Bash Read license: MIT metadata: version: "0.1.2" --- <!-- 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 1. **Freeze the observation** — write the exact observation before interpreting. Distinguish what was measured from what is inferred. Timestamp the observation date. 2. **Frame the research question** — restate as a falsifiable engineering question. Identify the claim type: descriptive, associational, predictive, causal, or mechanistic. 3. **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". 4. **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. 5. **Declare claim type and estimand** — specify what would be measured, the expected direction/magnitude, and the population/context where it applies. 6. **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?). 7. **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`: ```markdown # 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 yet ``` Write `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`, not `inferred`. - Evidence quality: see `references/evidence-quality-tiers.md`.
Wersje
| Repozytorium | Wynik | Licencja |
|---|---|---|
| Ta strona · adeerkhan/vitruvius | 100 | MIT |
| foryourhealth111-pixel/Vibe-Skills | 100 | Apache-2.0 |
| PracticalSwan/agent-skills | 100 | MIT |
| K-Dense-AI/scientific-agent-skills | 100 | MIT |
| mkurman/zorai | 100 | MIT |
| agent-skills-hub/agent-skills-hub | 100 | MIT |
| aipoch/medical-research-skills | 100 | MIT |
| pradyumnasagar/open-research-skills | 100 | MIT |
| aviskaar/open-org | 90 | Apache-2.0 |
Migawka bazy z 28.10.2026 · wersja paczki e9112cd1900b (skrót SHA-256 całej paczki)
Pobrania w ostatnich 30 dniach: 0 · ranking
Zgłoś problem z tym skillem: szkodliwa treść, błędny opis albo prośba autora o usunięcie.
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