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Skill

/coverage-white-space-search

Map known methods against problem/parameter space and generate candidates from uncovered intersections. Acquisition mechanism is runtime-selected.

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de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill coverage-white-space-search --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/coverage-white-space-search

Context preview

The summary Claude sees to decide when to auto-load this skill.

Map known methods against problem/parameter space and generate candidates from uncovered intersections. Acquisition mechanism is runtime-selected.

SKILL.md

coverage-white-space-search.SKILL.md
name: coverage-white-space-search
description: "Map known methods against problem/parameter space and generate candidates from uncovered intersections. Acquisition mechanism is runtime-selected."

coverage-white-space-search

Purpose

Map known methods against a problem space and generate candidates from uncovered intersections.

Input contract

required: [reference_items, coverage_dimensions]
optional: [performance_records, eligibility_rules]
constraints: [reference items and dimension values must be identifiable]

Execution protocol

Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.

1. You MUST load skill `inventory-reference-items` to inventory references. 2. You MUST load skill `map-coverage-space` to map coverage. 3. You MUST load skill `detect-coverage-gap` to detect uncovered regions. 4. You MUST load skill `synthesize-idea` to synthesize candidates. If a candidate gap is ready to become a testable explanation, consider `formulate-hypotheses`. If the gap itself still requires evidence validation, consider `validate-research-gap`. Deviation: acquisition is runtime-selected; do not infer coverage from missing records.

Output contract

produces: [reference_inventory, coverage_map, white_space_gaps, candidate_ideas]
delta_fields: [findings, evidence_updates, hypothesis_updates, decisions, open_questions]

Thresholds and quality gates

  • B: every reported gap is an explicit uncovered intersection over the declared dimensions; duplicate or ineligible regions are excluded.

Failure and counterexamples

Do not label a region white space when it is merely unsearched, incomparable, or outside the declared universe.

Provenance map

  • `systematic-enumeration`, `benchmark-sweep`, `coverage-analysis`, `white-space-identification`, `benchmark-inventory`, `coverage-gap-detection`, `white-space-detection`: resolved/concept by exact lookup.
  • Status: all except `benchmark-inventory` resolved; `benchmark-inventory` concept (only package-prefixed variant found).

Preserved source criteria ledger

  • Preserve inventory -> coverage crossing -> gap detection -> candidate synthesis.

Context checkpoint / Delta notes

Append inventory additions, occupied cells, gap definitions, exclusions, and generated candidates.

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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.

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