abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Intervene on factors, construct counterfactual worlds, test necessity/sufficiency, and identify load-bearing causal factors.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill counterfactual-causal-analysis --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/counterfactual-causal-analysisContext preview
The summary Claude sees to decide when to auto-load this skill.
Intervene on factors, construct counterfactual worlds, test necessity/sufficiency, and identify load-bearing causal factors.
name: counterfactual-causal-analysis description: "Intervene on factors, construct counterfactual worlds, test necessity/sufficiency, and identify load-bearing causal factors."
Intervene on factors, construct counterfactual worlds, test necessity and sufficiency, and identify load-bearing causal factors.
required: [causal_claim, variables, intervention_target] optional: [mechanism_graph, baseline_world, comparison_conditions] constraints: [intervention and outcome must be measurable or explicitly qualitative]
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
1. You MUST load skill `extract-causal-structure` to extract the causal structure. You MUST load skill `identify-variables` to type its variables. 2. You MUST load skill `construct-counterfactual` to construct the counterfactual. You MUST load skill `identify-load-bearing-factors` to identify load-bearing factors. 3. You MUST load skill `search-minimal-flip` to search the minimal conclusion flip. You MUST load skill `evaluate-necessity-sufficiency` to test necessity and sufficiency. If the conclusion should instead be tested by contradiction and counterexample, consider `reductio-counterexample-analysis` as the next tactic. Deviation: use qualitative counterfactuals when intervention data are unavailable, but mark the inference uncertainty.
produces: [causal_structure, counterfactual_map, load_bearing_factors, minimal_flip, necessity_sufficiency_report] delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties, decisions]
Do not call a factor necessary when an untested substitute can produce the outcome. Mark counterfactuals underdetermined when held-fixed conditions are unspecified.
| source | source line | kind | source criterion | |---|---:|---|---| | v4 architecture | node desc | textual | Intervene, construct counterfactual worlds, test necessity/sufficiency, identify load-bearing factors. |
Append intervention worlds, held-fixed conditions, factor ranking, flip search, and necessity/sufficiency results.
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.