Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill generate-competing-hypothesesAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
generate-competing-hypotheses
Purpose
Generate distinct, testable hypotheses that explain a target observation or research problem.
Input contract
yaml
required: [problem_statement, observations, scope_constraints]
optional: [existing_theories, analogies, anomaly_records]
constraints: [each hypothesis must imply a differentiating prediction or assumption]Procedure
- Extract the target phenomenon and unresolved explanatory gap.
- Generate mechanismally distinct explanations, including a null or status-quo hypothesis.
- Translate each explanation into predictions, assumptions, and disconfirming observations.
- Deduplicate equivalent explanations and retain the comparison set.
If competing hypotheses have explicit predictions and evidence links, consider score-object as the next tactic.
Output contract
yaml
produces: [hypothesis_set, mechanism_descriptions, prediction_set, assumption_register]
delta_fields: [hypothesis_updates, uncertainties, open_questions, recommended_jumps]Quality gates
- Hypotheses differ in mechanism or prediction, not wording only.
- A null or baseline explanation is considered where applicable.
Failure and counterexamples
Do not generate unfalsifiable narratives or discard inconvenient hypotheses before comparison.
Provenance map
resolved: generate-competing-hypotheses
