yogsoth-ai/de-anthropocentric-research-engine

categorize-evidence

Cluster an evidence corpus by theme, method, chronology, mechanism, or another declared schema.

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 categorize-evidence

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.

categorize-evidence

Purpose

Cluster an evidence corpus by a declared thematic, methodological, chronological, mechanistic, or other schema.

Input contract

yaml
required: [evidence_records, category_schema]
optional: [coding_rules, multi_label_policy, seed_categories]
constraints: [category assignments require record evidence and allow explicit multi-label or unknown states]

Procedure

  1. Define category semantics and assignment rules.
  2. Code each record using the declared evidence fields.
  3. Review boundary cases and preserve multi-label or unresolved assignments.
  4. Summarize category coverage and representative records.

If categorized sources now need claim-level structured records, consider extract-evidence-record as the next tactic.

Output contract

yaml
produces: [categorized_corpus, category_definitions, boundary_cases, coverage_summary]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]

Quality gates

  • Categories are mutually interpretable even when not mutually exclusive.
  • Every assignment is traceable to record fields.

Failure and counterexamples

Do not force records into categories whose definitions do not fit, and do not confuse frequency with evidential importance.

Provenance map

  • resolved: knowledge-acquisition-categorize-papers
  • concept: knowledge-structuring/source-categorization-patterns
  • intermediate: Pass4/map-field-taxonomy

Verwandte Aufgaben

aus demselben Repository

Weitere Skills

Alle Skills