yogsoth-ai/de-anthropocentric-research-engine

validate-causal-link

Audit a causal relation for clarity, existence, sufficiency, and logical completeness using CLR-style checks.

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 validate-causal-link

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.

validate-causal-link

Purpose

Audit a causal relation for clarity, existence, sufficiency, and logical completeness using CLR-style checks.

Input contract

yaml
required: [causal_relation, source_evidence, boundary_conditions]
optional: [causal_graph, alternative_explanations, clr_checklist]
constraints: [the relation has explicit cause and effect; distinguish clarity, existence, sufficiency, and logical completeness]

Procedure

  1. Parse the causal relation and define its scope and terms.
  2. Check whether the stated cause exists and is connected to the effect.
  3. Test sufficiency, omitted conditions, and alternative explanations.
  4. Record each CLR result and return a validated, weakened, or unresolved link.

Output contract

yaml
produces: [causal_link_assessment, clr_results, missing_conditions, evidence_requests]
delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties]

Quality gates

  • All eight CLR categories are retained when the caller supplies the full checklist.
  • Clarity, existence, sufficiency, and logical completeness are reported separately.
  • A causal label is not accepted when evidence supports only association.

Parameterization

The caller must provide the cause/effect schema, evidence and boundary conditions, CLR checklist, alternative-explanation fields, and verdict vocabulary.

Failure and counterexamples

Reject links with undefined variables, missing scope, circular support, or causal language unsupported by the evidence.

Provenance map

  • resolved: deep-insight/clr-validation

Preserved source criteria ledger

sourcephysical linekindsource criterion
deep-insight/clr-validation13structuralRetain eight CLR validation categories for causal claims: clarity, existence, sufficiency, and logical completeness are explicit checks.

Verwandte Aufgaben

aus demselben Repository

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