abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Extract a repeatable empirical pattern from observations, state its support and exceptions, and generalize cautiously without importing an unsupported mechanism.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill extract-empirical-regularity --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/extract-empirical-regularityContext preview
The summary Claude sees to decide when to auto-load this skill.
Extract a repeatable empirical pattern from observations, state its support and exceptions, and generalize cautiously without importing an unsupported mechanism.
name: extract-empirical-regularity description: "Extract a repeatable empirical pattern from observations, state its support and exceptions, and generalize cautiously without importing an unsupported mechanism."
Extract a repeatable empirical pattern from records while preserving conditions, exceptions, and uncertainty.
required: [observations, variable_schema, condition_schema] optional: [replication_records, measurement_uncertainty] constraints: [regularity claims require multiple comparable observations or an explicit single-case limitation]
1. Normalize observations, units, and conditions. 2. Identify repeated associations, trends, or invariants. 3. Test exceptions, alternative explanations, and measurement artifacts. 4. State the regularity with scope and uncertainty boundaries.
If the regularity is stable enough to express through measurable factors and outcomes, consider `identify-variables` as the next tactic.
produces: [regularity_statement, supporting_records, exception_set, scope_conditions] delta_fields: [findings, evidence_updates, uncertainties, open_questions]
Do not generalize a pattern across changed populations or protocols without a comparability check.
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.