abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Estimate sample/repetition requirements from detectable effect, uncertainty, power/precision target, and design structure.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-sample-size --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/estimate-sample-sizeContext preview
The summary Claude sees to decide when to auto-load this skill.
Estimate sample/repetition requirements from detectable effect, uncertainty, power/precision target, and design structure.
name: estimate-sample-size description: "Estimate sample/repetition requirements from detectable effect, uncertainty, power/precision target, and design structure."
Estimate sample/repetition requirements from detectable effect, uncertainty, power/precision target, and design structure.
required: [effect_target, uncertainty_model, power_target, design_structure] optional: [evidence, assumptions, prior_results] constraints: [use named scientific objects; retain provenance and missingness; $\alpha$ = 0.05 and power = 0.8 where applicable]
1. Validate the typed inputs and state the decision this operation must support. 2. Apply the declared operation to the named object; record intermediate values that affect interpretation. 3. Check boundary conditions and counterexamples, then emit the result with uncertainty and source links.
If the precision or power requirement is fixed, consider `select-statistical-method` as the next tactic.
produces: [estimate_sample_size_result, evidence_trace, uncertainties] delta_fields: [evidence_updates, uncertainties]
Return a failed operation with the violated precondition when inputs are incomplete, assumptions are unsupported, or a counterexample defeats the result.
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.