yogsoth-ai/de-anthropocentric-research-engine

list-undesirable-effects

List observable undesirable effects with evidence and severity as starting points for constraint/root-cause analysis.

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 list-undesirable-effects

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.

list-undesirable-effects

Purpose

List observable undesirable effects with evidence and severity as starting points for constraint/root-cause analysis.

Input contract

yaml
required: [system_observations, effect_evidence, severity_scale]
optional: [evidence, assumptions, prior_results]
constraints: [use named scientific objects; retain provenance and missingness; $\alpha$ = 0.05 and power = 0.8 where applicable]

Procedure

  1. Validate the typed inputs and state the decision this operation must support.
  2. Apply the declared operation to the named object; record intermediate values that affect interpretation.
  3. Check boundary conditions and counterexamples, then emit the result with uncertainty and source links.

Output contract

yaml
produces: [list_undesirable_effects_result, evidence_trace, uncertainties]
delta_fields: [evidence_updates, uncertainties]

Quality gates

  • Inputs are named scientific objects with compatible schemas.
  • Every material result has a derivation or source reference.
  • Fixed statistical criteria remain exact where applicable: $\alpha$ 0.05 and power 0.8.

Failure and counterexamples

Return a failed operation with the violated precondition when inputs are incomplete, assumptions are unsupported, or a counterexample defeats the result.

Provenance map

  • intermediate: experiment-execution/undesirable-effect-listing

Verwandte Aufgaben

aus demselben Repository

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