/aggregation-method
Aggregate multiple ranking ballots into a consensus ranking using a specified
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill aggregation-method --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/aggregation-method
Context preview
The summary Claude sees to decide when to auto-load this skill.
Aggregate multiple ranking ballots into a consensus ranking using a specified
SKILL.md
aggregation-method.SKILL.mdname: aggregation-method description: Aggregate multiple ranking ballots into a consensus ranking using a specified social choice method. execution: subagent prompt: ./prompt.md input: ballots(array), method(string) dependencies: sops: - spawn-agent
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).
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Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |
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The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.
Repo: yogsoth-ai/de-anthropocentric-research-engine
Other skills on de-anthropocentric-research-engine.
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Closing skill for the research-executor, loaded as the last step of formated-specs. Summarize the design just produced into one research-result JSON fenced block in your reply. Do not execute the research.
Open skill - /formated-specs
Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply. Replaces the generic spec-writing step.
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Open skill - /ladder-quality-order
Loss-2 judge (codex role). Over one topic's 6 shuffled research-design samples, pairwise-rank by quality using the D1–D5 standard. Emit the pairwise log; the harness computes the order and the ladder verdicts. Judge quality difference, never against academic standards.
Open skill - /optimization-loop
The optimizer brain for the ladder-foundry pretraining loop. Runs the two-level nested batch loop, delegates gating to gate_eval, attributes a failing batch to one weight (attribute-first), and recovers from disk after compaction. Control flow is fully scripted; only the
Open skill - /acu-nugget-recall
Tactic: Extract atomic units from one paper and score how much of a caller-supplied summary covers. Use for ACU-style binary or Nugget-style ternary recall checks; cannot run without a target summary.
Open skill