abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Map a set of methods/assets/evidence items against a typed problem, capability, condition, or design space to expose redundancy, coverage structure, and the strength of support in each occupied region.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill map-coverage-space --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill map-coverage-space -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill map-coverage-space -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill map-coverage-space -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill map-coverage-space -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill map-coverage-space -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill map-coverage-space -a windsurf -y
name: map-coverage-space description: "Map a set of methods/assets/evidence items against a typed problem, capability, condition, or design space to expose redundancy, coverage structure, and the strength of support in each occupied region."
Map methods, assets, or evidence against a typed problem or capability space to expose redundancy, gaps, and how strongly each occupied region is supported.
required: [item_set, coverage_dimensions, target_space] optional: [strength_scale, applicability_rules, evidence_links] constraints: [dimension semantics and coverage states are declared]
1. Define cells or regions from the supplied dimensions. 2. Assign each item to the regions it occupies, with evidence. 3. Grade every occupied region on the caller's strength scale, or on supported, partial, or unsupported when none is supplied; a region graded below the top names what it lacks. 4. Merge duplicate coverage and identify uncovered and weakly supported regions. 5. Return the map with evidence, strength grades, and confidence annotations.
If expected and observed coverage are represented on the same space, consider `detect-coverage-gap` as the next tactic.
produces: [coverage_map, redundancy_clusters, gap_register, confidence_annotations] delta_fields: [findings, evidence_updates, uncertainties]
Caller supplies item schema, dimension ontology, coverage states, strength scale, and audit numerator/denominator definitions.
Reject maps with implicit dimensions, unsupported assignments, ungraded occupancy, or ratios lacking a declared universe.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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