detect-coverage-gap

SkillDev tools

Lets your agent analyze a matrix, graph, or taxonomy to find missing or weakly covered areas and explain why they matter.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the detect-coverage-gap skill

About this skill

Given an explicit coverage representation (matrix, graph, taxonomy, IP feature space), identify absent, thin, disconnected, or weakly covered regions and characterize why they matter.

What this skill tells your AI

The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/detect-coverage-gap/SKILL.md and read by ahel’s review.

Purpose

Given an explicit matrix, graph, taxonomy, or IP feature space, identify absent, thin, disconnected, or weakly covered regions and explain why they matter.

Input contract

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]

Procedure

  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.

Output contract

produces: [coverage_gap_list, coverage_map, priority_rationale, evidence_register]
delta_fields: [findings, evidence_updates, decisions, open_questions]

Quality gates

  • Declare the eligible universe, numerator, denominator, batch increment, stopping reason, source references, direction, and threshold rationale for relative coverage claims.
  • Report coverage ratio whenever a relative coverage claim is made.
  • When coverage is evaluated over evidence sources or batches, also report independent-source ratio, marginal information gain, and saturation state.
  • The complete orphan list is analyzed where graph mode applies; weak links below <0.3 are retained as source-defined evidence and not silently normalized.
  • Matrix white-space detection and graph orphan detection remain distinct representations.

Parameterization

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.

Failure and counterexamples

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.

Provenance map

  • resolved: creative-ideation/coverage-gap-detection
  • resolved: creative-ideation/white-space-detection
  • resolved: knowledge-acquisition/white-space-mapping
  • resolved: knowledge-structuring/gap-detection
  • resolved: knowledge-structuring/model-gap-detection
  • intermediate: Pass3/detect-white-space
  • intermediate: Pass3/map-ip-white-space
  • intermediate: Pass3/detect-structural-gap

Verbatim source criteria excerpts

  • gap-detection line 27: Must analyze the full orphan list and report actionable gap descriptions.
  • model-gap-detection line 21: Check for edges with weight < 0.3 - these are weak links needing more evidence.
  • model-gap-detection line 27: Must check both orphans and weak links and include actionable suggestions.

Preserved source criteria ledger

sourcephysical linekindsource criterion
knowledge-structuring/gap-detection14gateAnalyze the complete orphan list and provide executable repair suggestions.
knowledge-structuring/model-gap-detection14numeric/gateQuery orphan nodes with degree 0 and weak links <0.3; provide executable gaps and suggestions.

Signals

GitHub stars
501
Forks
41
Last commit
Sep 2026
Advanced
Catalog kind
skill
Key
detect-coverage-gap
Source
github.com/yogsoth-ai/de-anthropocentric-research-engine