conceptual-blending

SkillDev tools

Lets your agent combine ideas from two or more fields to generate new research concepts neither field alone would suggest.

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 conceptual-blending skill

About this skill

Construct multiple input spaces, extract a shared generic space, selectively project structure into a blend, and simulate emergent properties that are not present in either source alone.

What this skill tells your AI

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

Purpose

Blend multiple input spaces through a generic space and selective projection to generate emergent research ideas.

Input contract

mode_contracts:
  two-space-blend: &blending_input
    required: [input_spaces]
    optional: [compatibility_constraints]
    constraints: [each_input_space_must_have_explicit_entities_and_relations]
  multi-space-blend: *blending_input
  emergent-property-search: *blending_input

Execution protocol

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

  1. You MUST load skill construct-input-spaces to construct the input spaces.
  2. You MUST load skill extract-generic-space to extract the generic space.
  3. You MUST load skill simulate-emergent-properties to simulate emergent properties.
  4. You MUST load skill evaluate-compatibility to check compatibility.
  5. You MUST load skill synthesize-idea to synthesize the blend. If the blend should be explored across a systematic combination space, consider explore-dimensional-space. If its claimed structural transfer needs formal testing, consider audit-structural-equivalence. Deviation: two-space and multi-space modes change only the number of inputs; generic-space extraction is mandatory.

Mode branches

  • two-space-blend: blend two explicit input spaces.
  • multi-space-blend: blend three or more spaces while preserving each projection trace.
  • emergent-property-search: prioritize properties absent from every source space alone.

Output contract

mode_contracts:
  two-space-blend: &space_blend_output
    produces: [input_space_set, generic_space, blend_candidates, idea_set]
    delta_fields: [findings, hypothesis_updates, uncertainties, decisions, open_questions]
  multi-space-blend: *space_blend_output
  emergent-property-search:
    produces: [input_space_set, blend_candidates, emergent_property_report, idea_set]
    delta_fields: [findings, hypothesis_updates, uncertainties, decisions, open_questions]

Thresholds and quality gates

  • B: all source spaces and projected relations are recorded; emergent properties must be absent from each source alone and compatible with target constraints.

Failure and counterexamples

Reject mere juxtaposition, unsupported emergence claims, and blends with unresolved relation conflicts.

Provenance map

  • creative-ideation/combinatorial-creativity, conceptual-blending, emergent-property-hunting: resolved/concept per exact v3 lookup.
  • Status: creative-ideation/combinatorial-creativity, emergent-property-hunting resolved; conceptual-blending concept (no exact v3 node).

Preserved source criteria ledger

  • Preserve generic-space construction, selective projection, and emergent-property semantics.

Context checkpoint / Delta notes

Append source-space changes, projected relations, emergence claims, compatibility findings, and selected ideas.

Signals

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