abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Test whether an elegant/simple explanation earns its compression by forbidding alternatives, subsuming independent facts, or making risky predictions, rather than merely relabeling observations with a compact vocabulary.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill audit-explanatory-compression --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/audit-explanatory-compressionContext preview
The summary Claude sees to decide when to auto-load this skill.
Test whether an elegant/simple explanation earns its compression by forbidding alternatives, subsuming independent facts, or making risky predictions, rather than merely relabeling observations with a compact vocabulary.
name: audit-explanatory-compression description: "Test whether an elegant/simple explanation earns its compression by forbidding alternatives, subsuming independent facts, or making risky predictions, rather than merely relabeling observations with a compact vocabulary."
Test whether an elegant explanation earns compression by excluding alternatives, subsuming independent facts, or making risky predictions.
mode_contracts:
earned-simplicity: &compression_audit_input
required: [explanation, covered_facts, alternatives]
optional: [predictions, evidence]
constraints: [facts_and_alternatives_must_be_independently_enumerated]
decorative-simplicity: *compression_audit_input
risky-prediction: *compression_audit_inputDo not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
1. You MUST load skill `classify-simplicity-evidence` to classify the explanation's compression evidence. 2. You MUST load skill `test-risky-prediction` to derive and test risky predictions. 3. You MUST load skill `construct-critique` to attack the explanation. You MUST load skill `score-object` to score its remaining support. Deviation: omit prediction testing only when no nontrivial prediction can be derived, and mark the explanation non-discriminating.
mode_contracts:
earned-simplicity: &compression_audit_output
produces: [forbidden_set, risky_predictions, accommodation_audit, deletion_test_result, elegance_verdict, earning_prediction]
delta_fields: [findings, evidence_updates, uncertainties, decisions]
decorative-simplicity: *compression_audit_output
risky-prediction: *compression_audit_outputDo not reward brevity alone. Mark weak when independent facts, exclusions, or predictions are absent.
| source | source line | kind | source criterion | |---|---:|---|---| | v4 architecture | node desc | textual | Distinguish earned simplicity from decorative relabeling. |
Append covered facts, alternatives, risky predictions, critique, and score rationale.
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.
Evaluate competing arguments against stated criteria and produce a reasoned verdict with uncertainty.
Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context, outcome, timeframe, system…
Run structured attack/defense/adjudication over a claim, candidate, criterion set, or current winner. Perspective, target, escalation depth,…
Aggregate criterion or comparison results into an ordered recommendation under an explicit rule.
Abstract relational structure from source domains, map it to the target, validate depth, and instantiate transferable mechanisms.