Como usar
- Copie o comando e verifique o pacote antes de instalar no seu ambiente de agente.
- Consulte no original as ferramentas, credenciais e ambientes necessários.
- Descreva os dados de entrada e a entrega esperada; confira a saída com as fontes.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill detect-feedback-loopAntes de começar
- A instalação não inclui assinatura de modelo, franquia API ou acesso aos seus arquivos.
- Estrelas e instalações indicam atividade, não um teste independente de qualidade ou segurança.
Documento original do Skill
Renderizado do repositório de origem, preservando títulos, exemplos, código, tabelas, links e imagens.
detect-feedback-loop
Purpose
Detect reinforcing or balancing feedback loops in a causal or process structure and state the evidence for each loop.
Input contract
yaml
required: [causal_graph, node_semantics, edge_polarity]
optional: [time_delays, observed_series, intervention_records]
constraints: [loop classification requires directed edges and polarity or transition evidence]Procedure
- Normalize directed relations, polarity, and delays.
- Enumerate simple cycles and identify reinforcing or balancing sign patterns.
- Compare loops with observations or intervention evidence where available.
- Report loop boundaries, uncertain edges, and testable implications.
Output contract
yaml
produces: [feedback_loops, loop_classification, supporting_evidence, uncertain_edges, testable_implications]
delta_fields: [findings, evidence_updates, uncertainties, recommended_jumps]Quality gates
- Every loop lists its ordered edges and polarity basis.
- Correlational cycles are not presented as causal loops without qualification.
Failure and counterexamples
Do not infer feedback from a static co-occurrence or omit time direction where it determines loop meaning.
Provenance map
resolved: detect-feedback-loop
