abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Normalize heterogeneous values onto a declared comparison scale while preserving direction, units, uncertainty, and the transformation rule. The normalized object may be criterion scores, resource budgets, or another comparable quantity.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill normalize-comparison-scale --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/normalize-comparison-scaleContext preview
The summary Claude sees to decide when to auto-load this skill.
Normalize heterogeneous values onto a declared comparison scale while preserving direction, units, uncertainty, and the transformation rule. The normalized object may be criterion scores, resource budgets, or another comparable quantity.
name: normalize-comparison-scale description: "Normalize heterogeneous values onto a declared comparison scale while preserving direction, units, uncertainty, and the transformation rule. The normalized object may be criterion scores, resource budgets, or another comparable quantity."
Normalize heterogeneous values onto a declared comparison scale while preserving direction, units, uncertainty, and transformation rule.
required: [value_set, criterion_definitions, normalization_rule] optional: [bounds, missing_value_policy, uncertainty_model] constraints: [direction and units are preserved; rule is declared before transformation]
1. Validate units, direction, bounds, and missingness. 2. Apply the caller-supplied transformation to each value. 3. Preserve uncertainty and retain original values for audit. 4. Return normalized values and out-of-bound diagnostics.
produces: [normalized_values, transformation_record, uncertainty_preservation, diagnostics] delta_fields: [evidence_updates, uncertainties, open_questions]
Caller supplies value schema, units, direction labels, bounds, transformation formula, and missingness policy.
Reject mixed units, hidden inversion, or normalization that discards uncertainty and source values.
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
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
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