abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Abstract relational structure from source domains, map it to the target, validate depth, and instantiate transferable mechanisms.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill analogical-discovery --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/analogical-discoveryContext preview
The summary Claude sees to decide when to auto-load this skill.
Abstract relational structure from source domains, map it to the target, validate depth, and instantiate transferable mechanisms.
name: analogical-discovery description: "Abstract relational structure from source domains, map it to the target, validate depth, and instantiate transferable mechanisms."
Transfer a validated relational structure from a source domain into a target research problem.
required: [target_problem, source_domain] optional: [candidate_sources, transfer_constraints] constraints: [source and target roles must be explicit]
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
1. You MUST load skill `abstract-structure` to abstract the relational structure. 2. You MUST load skill `map-analogy` to map source relations to the target. 3. You MUST load skill `instantiate-transfer` to instantiate and test the transferred mechanism. If the analogy should be expanded across a typed combination space, consider `explore-dimensional-space`. If biological mechanisms are the relevant source domain, consider `biomimetic-transfer`. If several source structures must be composed, consider `conceptual-blending`. If the claimed mapping requires a formal preservation audit, `audit-structural-equivalence` may be the better next tactic. Deviation: skip source search only when a supplied source is structurally specified; never skip mapping or transfer validation.
produces: [abstract_structure, structural_mapping, transfer_candidate] delta_fields: [findings, hypothesis_updates, uncertainties, decisions, open_questions]
Reject transfers whose causal/relational roles do not map, whose target constraints are violated, or whose claimed mechanism is only lexical resemblance.
Append source relations, mapping gaps, transfer assumptions, and validation findings.
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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