yogsoth-ai/de-anthropocentric-research-engine

select-critical-case

Select most-likely, least-likely, or otherwise inference-maximizing cases that can decisively support/refute a claim under explicit case-selection logic.

Vedi sorgente

Come usare

  1. Copia il comando e controlla il pacchetto prima di installarlo nel tuo ambiente agente.
  2. Controlla strumenti, credenziali e ambienti richiesti nel documento originale.
  3. Descrivi input e risultato desiderato; confronta l’output con le fonti.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill select-critical-case

Prima di iniziare

  • L’installazione non include abbonamenti, quote API o accesso ai file.
  • Stelle e installazioni indicano attività, non un test indipendente di qualità o sicurezza.
Documento Skill originale

Contenuto dal repository con titoli, esempi, codice, tabelle, link e immagini preservati.

select-critical-case

Purpose

Select most-likely, least-likely, or otherwise inference-maximizing cases that can decisively support or refute a claim.

Input contract

yaml
required: [claim, case_universe, selection_logic]
optional: [likelihood_model, boundary_conditions]
constraints: [case selection rule and inference purpose must be explicit]

Procedure

  1. Define the eligible case universe and selection objective.
  2. Rank cases under the declared logic.
  3. Select and justify the critical case, including excluded cases.

Output contract

yaml
produces: [critical_case, selection_rationale, excluded_cases, inference_role]
delta_fields: [findings, evidence_updates, uncertainties, decisions]

Quality gates

  • Selected case must be traceable to the stated selection logic.

Failure and counterexamples

Do not call a convenient case critical without comparing it to the declared universe.

Provenance map

  • resolved: critical-case-design
  • resolved: counterexample-heuristics
dallo stesso repository

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