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 extract-core-conflict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。
extract-core-conflict
Purpose
Represent a core constraint conflict in an Evaporating-Cloud-like structure with explicit assumptions on every dependency.
Input contract
yaml
required: [undesirable_effects, constraint_relations, assumption_records]
optional: [evidence, assumptions, prior_results]
constraints: [use named scientific objects; retain provenance and missingness; $\alpha$ = 0.05 and power = 0.8 where applicable]Procedure
- Validate the typed inputs and state the decision this operation must support.
- Apply the declared operation to the named object; record intermediate values that affect interpretation.
- Check boundary conditions and counterexamples, then emit the result with uncertainty and source links.
Output contract
yaml
produces: [extract_core_conflict_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/core-conflict-extraction
