abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Audit whether a research/evaluation artifact reports the information needed for interpretation and reproduction, using a domain-appropriate checklist.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill audit-reporting-quality --agent claude-codeHow it fires
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/audit-reporting-qualityContext preview
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Audit whether a research/evaluation artifact reports the information needed for interpretation and reproduction, using a domain-appropriate checklist.
name: audit-reporting-quality description: "Audit whether a research/evaluation artifact reports the information needed for interpretation and reproduction, using a domain-appropriate checklist."
Audit whether an artifact reports the information needed for interpretation and reproduction using a declared domain-appropriate checklist.
required: [artifact, reporting_checklist] optional: [domain_schema, reproduction_requirements, source_context] constraints: [each checklist judgment must cite present, absent, or ambiguous evidence]
1. Instantiate the checklist for the artifact type and domain. 2. Inspect each item and record evidence, omission, or ambiguity. 3. Separate interpretation-critical omissions from cosmetic omissions. 4. Summarize reporting completeness and reproduction implications.
produces: [checklist_results, critical_omissions, ambiguity_log, reporting_quality_summary] delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]
Do not equate a long report with complete reporting or treat an inapplicable checklist item as a failure.
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.
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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.