claim-label-prediction

Judge a three-way SUPPORTS/REFUTES/NOINFO label for an atomic claim, based only on its selected rationale sentences (SciFact's final classification step). Use this after rationale-selection has produced the evidence sentences — this is the terminal step of the SciFact chain, producing the complete (claim, abstract, label, rationale) tuple.

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Repositorio: yogsoth-ai/de-anthropocentric-research-engine
Última actividad en el origen: 8 de agosto de 2026 a las 04:26
Idioma detectado de SKILL.md: inglés
Estrellas: 373
Forks: 32

Opciones de instalación

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npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill claim-label-prediction

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SKILL.md

Instrucciones de origen · Vista previa de solo lectura

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adversarial-debate-truthseeking

Strategy: Dialectic engine retuned for truth-seeking, not survival. A defender steelmans a claim into its MOST falsifiable form, a critic attacks to refute it, a judge classifies the exchange into BROKEN/CORROBORATED/UNFALSIFIABLE — the judge does NOT pick a winner or score persuasiveness. Methods: Irving debate (repurposed), Toulmin argumentation, Mayo severe testing.

2026-08-09

adversarial-stress-testing

Campaign: Logical extreme and boundary testing via reductio ad absurdum and edge-case analysis. Core question: Does this artifact collapse under logical limits and boundary conditions? Methods: Lakatos 1976, Dutilh Novaes 2016, BVA, Flyvbjerg Critical Case, Popper.

2026-08-09

argument-mapping

Campaign for mapping argument structures — extract claims, link evidence, assess strength, synthesize positions. Produces argument graphs in the wiki vault.

2026-08-09

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name	claim-label-prediction
description	Judge a three-way SUPPORTS/REFUTES/NOINFO label for an atomic claim, based only on its selected rationale sentences (SciFact's final classification step). Use this after rationale-selection has produced the evidence sentences — this is the terminal step of the SciFact chain, producing the complete (claim, abstract, label, rationale) tuple.
version	1.0.0
category	paper-reading
type	sop
execution	subagent
prompt	./prompt.md
input	atomic_claim (string), rationale_sentences (list of strings)
output	label (string: "SUPPORTS" \| "REFUTES" \| "NOINFO")
dependencies	{"sops":["spawn-agent"]}

name	claim-label-prediction
description	Judge a three-way SUPPORTS/REFUTES/NOINFO label for an atomic claim, based only on its selected rationale sentences (SciFact's final classification step). Use this after rationale-selection has produced the evidence sentences — this is the terminal step of the SciFact chain, producing the complete (claim, abstract, label, rationale) tuple.
version	1.0.0
category	paper-reading
type	sop
execution	subagent
prompt	./prompt.md
input	atomic_claim (string), rationale_sentences (list of strings)
output	label (string: "SUPPORTS" \| "REFUTES" \| "NOINFO")
dependencies	{"sops":["spawn-agent"]}

claim-label-prediction

Opciones de instalación

Revisa los archivos de origen