abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Given an explicit coverage representation (matrix, graph, taxonomy, IP feature space), identify absent, thin, disconnected, or weakly covered regions and characterize why they matter.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-coverage-gap --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/detect-coverage-gapContext preview
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Given an explicit coverage representation (matrix, graph, taxonomy, IP feature space), identify absent, thin, disconnected, or weakly covered regions and characterize why they matter.
name: detect-coverage-gap description: "Given an explicit coverage representation (matrix, graph, taxonomy, IP feature space), identify absent, thin, disconnected, or weakly covered regions and characterize why they matter."
Given an explicit matrix, graph, taxonomy, or IP feature space, identify absent, thin, disconnected, or weakly covered regions and explain why they matter.
required: [coverage_representation, universe_definition, coverage_evidence] optional: [gap_priority_rule, taxonomy, graph_statistics, domain_constraints] constraints: [the representation and eligible universe are explicit; every reported gap points to an absent, thin, disconnected, or weakly covered region]
1. Validate the representation and enumerate its eligible regions or nodes. 2. Mark observed coverage and classify absent, thin, disconnected, and weak-link regions. 3. Characterize the consequence and evidence for each gap. 4. Prioritize gaps using the caller-supplied rule and return an actionable gap list.
produces: [coverage_gap_list, coverage_map, priority_rationale, evidence_register] delta_fields: [findings, evidence_updates, decisions, open_questions]
The caller must provide the coverage representation type, eligible universe, observed evidence, region/node schema, thinness or connectivity rule, priority rule, and source references. For graph mode provide node/edge statistics; for IP mode provide the feature taxonomy and claim map.
Reject when the universe is undefined, a gap is inferred from missing data rather than represented absence, or an orphan/weak-link result lacks a repair rationale.
| source | physical line | kind | source criterion | |---|---:|---|---| | knowledge-structuring/gap-detection | 14 | gate | Analyze the complete orphan list and provide executable repair suggestions. | | knowledge-structuring/model-gap-detection | 14 | numeric/gate | Query orphan nodes with degree 0 and weak links `<0.3`; provide executable gaps and suggestions. |
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
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