使い方
- インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
- 必要なツール、認証情報、対応環境を原文で確認します。
- 入力と成果物を指定し、出力を資料と照合します。
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill detect-feedback-loop開始前の確認
- 導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
- スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。
リポジトリの原文
見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。
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
