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/explore-dimensional-space

Represent a problem/research space as validated dimensions and values, enumerate compatible combinations, and optionally map occupancy, detect gaps, prioritize regions, or synthesize candidate questions/ideas.

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de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill explore-dimensional-space --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/explore-dimensional-space

Context preview

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

Represent a problem/research space as validated dimensions and values, enumerate compatible combinations, and optionally map occupancy, detect gaps, prioritize regions, or synthesize candidate questions/ideas.

SKILL.md

explore-dimensional-space.SKILL.md
name: explore-dimensional-space
description: "Represent a problem/research space as validated dimensions and values, enumerate compatible combinations, and optionally map occupancy, detect gaps, prioritize regions, or synthesize candidate questions/ideas."

explore-dimensional-space

Purpose

Represent a problem space as validated dimensions and values, enumerate compatible combinations, map occupancy, detect gaps, and synthesize candidate questions or ideas.

Input contract

mode_contracts:
  morphological-generation: &dimensional_input
    required: [target_space, dimensions, values]
    optional: [coverage_matrix, compatibility_rules, objective]
    constraints: [dimension_semantics_and_independence_posture_must_be_declared]
  research-space-mapping: *dimensional_input
  gap-mapping: *dimensional_input

Execution protocol

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

1. You MUST load skill `define-analysis-dimensions` to define the exploration axes. You MUST load skill `enumerate-dimension-values` to enumerate meaningful values. 2. Apply the selected mode's combination, compatibility, and coverage operations. 3. Retain axis dependencies and uncovered regions exposed by the selected mode. 4. When the task is not descriptive mapping, You MUST load skill `score-object` to score the retained regions. When a research question is in scope, You MUST load skill `generate-subquestions` to derive questions from those regions. If deliberate disruption is needed to escape the declared axes, consider `destructive-ideation`. If the main objective becomes systematic coverage repair, `coverage-white-space-search` may be the better next tactic. Deviation: skip scoring when the task is descriptive mapping; skip subquestions when no research question is in scope.

Output contract

mode_contracts:
  morphological-generation:
    produces: [dimension_schema, value_catalog, combination_map, compatibility_report]
    delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties, decisions, recommended_jumps]
  research-space-mapping:
    produces: [dimension_schema, value_catalog, coverage_gaps, prioritized_regions, subquestions]
    delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties, decisions, recommended_jumps]
  gap-mapping:
    produces: [coverage_gaps, prioritized_regions, subquestions]
    delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties, decisions, recommended_jumps]

Thresholds and quality gates

  • Axis independence, compatibility rules, and gap representation must be inspectable.
  • Scores require a declared rubric and evidence.

Failure and counterexamples

Do not call a sparse matrix a white space until compatibility and coverage semantics are checked. Merge redundant axes rather than double-counting them.

Provenance map

  • resolved: morphological-exploration
  • resolved: general-morphological-analysis
  • resolved: cross-consistency-analysis
  • concept: combination-mapping [tactic]
  • concept: consistency-checking [tactic]
  • resolved: dimensional-analysis
  • concept: axis-identification [strategy]
  • concept: combination-mapping [strategy]
  • concept: gap-prioritization [strategy]
  • resolved: matrix-generation
  • intermediate: Pass5/morphological-search
  • intermediate: Pass5/map-dimensional-research-space

Preserved source criteria ledger

| source | source line | kind | source criterion | |---|---:|---|---| | v4 architecture | node desc | textual | Enumerate compatible combinations, validate axes, map occupancy and detect gaps. |

Context checkpoint / Delta notes

Append dimensions, values, combinations, pruned regions, gaps, scores, and derived questions.

Mode branches

  • `morphological-generation`: emphasize unconstrained combination generation before pruning. You MUST load skill `enumerate-combinations` to enumerate the combinations. You MUST load skill `evaluate-compatibility` to prune incompatible combinations.
  • `research-space-mapping`: emphasize typed dimensions, occupancy, and coverage. You MUST load skill `validate-axis-independence` to identify dependent axes.
  • `gap-mapping`: emphasize absent/thin/disconnected regions and their implications. You MUST load skill `detect-coverage-gap` to identify absent, thin, and disconnected regions.
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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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Repo: yogsoth-ai/de-anthropocentric-research-engine