yogsoth-ai/de-anthropocentric-research-engine

select-next-pair

Select the next comparison pair to maximize expected information gain.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill select-next-pair

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

select-next-pair

Purpose

Select the next comparison pair to maximize expected information gain while respecting unresolved uncertainty and coverage.

Input contract

yaml
required: [candidate_set, current_ratings, uncertainty_matrix, comparison_budget]
optional: [pair_history, exploration_policy, exclusion_constraints]
constraints: [candidate IDs are stable; expected information gain uses the declared model and available evidence]

Procedure

  1. Enumerate eligible unjudged pairs and compute their current uncertainty and decision relevance.
  2. Estimate expected information gain under the declared comparison model, including the value of resolving a tie or cycle.
  3. Exclude pairs blocked by scope or data constraints, then select the highest-value eligible pair.
  4. Return the selected pair, rationale, alternatives considered, and the budget impact.

Output contract

yaml
produces: [selected_pair, information_gain_estimate, candidate_pair_table, selection_rationale]
delta_fields: [findings, evidence_updates, uncertainties, decisions, recommended_jumps]

Quality gates

  • The selected pair is eligible, not already resolved under the same model, and has a stated information-gain rationale.
  • If all pairs are exhausted or blocked, return an explicit stop reason.

Failure and counterexamples

Do not select a pair solely because it is adjacent in a list. Expected information gain cannot be claimed when uncertainty inputs are absent.

Provenance map

  • resolved: pair-selector

Verwandte Aufgaben

aus demselben Repository

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