aggregation-method
This skill aggregates multiple ranked ballots into a single consensus ranking using social choice methods including Schulze, Borda, Kemeny-Young, Copeland, and Condorcet. Use it when you need to combine multiple preference orderings from voters or evaluators into a definitive group ranking, ensuring the output reflects genuine consensus properties like Condorcet consistency where applicable.
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine /tmp/aggregation-method && cp -r /tmp/aggregation-method/skills/aggregation-method ~/.claude/skills/aggregation-methodSKILL.md
# Aggregation Method Applies a social choice aggregation method to a set of ranking ballots to produce a consensus ranking. Supports Schulze, Borda, Kemeny-Young, Copeland, and Condorcet methods. ## Execution Runs as a subagent. Receives ballots and method specification, returns the aggregated consensus ranking. ## Why Subagent Aggregation algorithms (especially Kemeny-Young) involve combinatorial computation and method-specific logic. Isolating this ensures correct algorithm application and clear separation from collection and interpretation. ## HARD-GATE Output MUST produce a complete ranking of all candidates. The method field MUST match the input method. If a Condorcet winner exists, it MUST be ranked first (for Condorcet-consistent methods).
Experiment-specific - summarize the DARE executor's research design into a clean research_result report, forced to write back into the spec file produced by formated-specs.
Experiment-specific - replaces writing-specs, emits DARE's 4-layer call plan as a clean research_graph schema. Last step forces load formated-result.
loss-1 judge - read a sample's full dialogue and decide whether the user simulator semantically enacted its Policy Card. check-blind.
loss-2 judge - pairwise quality comparison across the n rungs within one topic; decide monotonicity and endpoint separation. check-blind, D1-D5 only.
Strategy: 面对异常的最佳解释推理
Remove components one by one, observe system changes to reveal hidden dependencies and generate ideas from structural gaps.
Map system architecture to ablatable units for ablation studies
Design ablation studies to isolate component contributions in ML systems