abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Define research questions, evidence scope, queries/concepts, inclusion/exclusion rules, provenance requirements, and stopping evidence for an acquisition task.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill define-evidence-protocol --agent claude-codeHow it fires
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Define research questions, evidence scope, queries/concepts, inclusion/exclusion rules, provenance requirements, and stopping evidence for an acquisition task.
name: define-evidence-protocol description: "Define research questions, evidence scope, queries/concepts, inclusion/exclusion rules, provenance requirements, and stopping evidence for an acquisition task."
Define research questions, eligible evidence scope, query concepts, inclusion/exclusion rules, provenance requirements, and stopping evidence.
required: [research_question, evidence_scope, inclusion_rules] optional: [exclusion_rules, query_concepts, quality_rubric, stopping_policy] constraints: [eligible universe, provenance fields, and stopping evidence must be explicit]
1. State the question, target population or domain, comparison, outcomes, and time boundaries. 2. Define eligible evidence, exclusion rules, source-independence requirements, and extraction fields. 3. Specify batch boundaries, novelty dimensions, and relative stopping evidence. 4. Record unresolved scope choices before acquisition begins.
If the protocol fixes inclusion, exclusion, and stopping rules, consider `select-seed-evidence` as the next tactic.
produces: [evidence_protocol, eligible_universe, query_concepts, screening_rules, provenance_requirements, stopping_evidence] delta_fields: [decisions, assumption_updates, uncertainties, open_questions]
Do not use provider names as a protocol, and do not declare coverage from search volume without a defined eligible universe.
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.