yogsoth-ai/de-anthropocentric-research-engine

aggregate-ranking

Aggregate criterion or comparison results into an ordered recommendation under an explicit rule.

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使い方

  1. 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。
  2. 必要なツール、認証情報、対応環境を原文で確認します。
  3. 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 aggregate-ranking

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。

aggregate-ranking

Purpose

Aggregate criterion or comparison results into an ordered recommendation under an explicit rule.

Input contract

yaml
required: [candidate_set, criterion_results, aggregation_rule]
optional: [tie_break_rule, missing_value_policy, uncertainty_annotations]
constraints: [criterion directions and scales must be declared; no silent imputation]

Procedure

  1. Align candidate identifiers, criterion directions, units, and validity flags.
  2. Apply the supplied aggregation rule without changing weights or directions.
  3. Propagate missingness and uncertainty; apply the declared tie-break only after aggregation.
  4. Return ordered candidates with component contributions and recommendation status.

Output contract

yaml
produces: [ordered_recommendation, aggregate_scores, contribution_table, unresolved_comparisons]
delta_fields: [findings, evidence_updates, decisions, uncertainties]

Quality gates

  • Every ranked candidate has a traceable value for each required criterion or an explicit unresolved marker.
  • Aggregation reproduces the supplied rule and preserves criterion direction.
  • Ties and sensitivity to tie-breaks are reported.

Parameterization

Caller supplies candidate schema, criterion scales/directions, weights or aggregation formula, tie-break rule, and missing/uncertainty policy.

Failure and counterexamples

Reject mixed units without normalization; reject a recommendation when a hard criterion is unresolved.

Provenance map

  • resolved: priority-synthesis
  • resolved: scoring-synthesis

Preserved source criteria ledger

sourcecriterion
priority-synthesisAll scoring dimensions are present for every gap.
priority-synthesisWeight vector sums to 1.0 within +/-0.001.
priority-synthesisPriority list is sorted descending; ties use feasibility sub-score.
priority-synthesisTop N is N=min(3,total gaps) and includes attack-path suggestions.
scoring-synthesisFinal recommendation includes recommended alternative, confidence, key assumptions, and risk warnings.

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