explore-dimensional-space
SkillDev toolsLets your agent break a problem into dimensions, list valid combinations, and spot unexplored gaps or new questions.
Available today. Use it from your connected AI after setup.
No other account needed.
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 explore-dimensional-space skill
About 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.
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/explore-dimensional-space/SKILL.md and read by ahel’s review.
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.
- You MUST load skill
define-analysis-dimensionsto define the exploration axes. You MUST load skillenumerate-dimension-valuesto enumerate meaningful values. - Apply the selected mode's combination, compatibility, and coverage operations.
- Retain axis dependencies and uncovered regions exposed by the selected mode.
- When the task is not descriptive mapping, You MUST load skill
score-objectto score the retained regions. When a research question is in scope, You MUST load skillgenerate-subquestionsto derive questions from those regions. If deliberate disruption is needed to escape the declared axes, considerdestructive-ideation. If the main objective becomes systematic coverage repair,coverage-white-space-searchmay 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 skillenumerate-combinationsto enumerate the combinations. You MUST load skillevaluate-compatibilityto prune incompatible combinations.research-space-mapping: emphasize typed dimensions, occupancy, and coverage. You MUST load skillvalidate-axis-independenceto identify dependent axes.gap-mapping: emphasize absent/thin/disconnected regions and their implications. You MUST load skilldetect-coverage-gapto identify absent, thin, and disconnected regions.
Signals
- GitHub stars
- 501
- Forks
- 41
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Key
explore-dimensional-space- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine