TypingMindTypingMindThe best frontend for AI
Conceptual Blending logo

Conceptual Blending

Organization
yogsoth-ai
conceptual-blending

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.

Overview

Publisheryogsoth-ai
Repositoryde-anthropocentric-research-engine
Skill nameconceptual-blending
Stars
505
Forks
43
Bundled files
Instructions only
LicenseApache-2.0
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by yogsoth-ai on GitHub. Read the source before you install it.

Installation

Install the Conceptual Blending AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/conceptual-blending
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git /tmp/de-anthropocentric-research-engine
mkdir -p .claude/skills
cp -r /tmp/de-anthropocentric-research-engine/skills/conceptual-blending .claude/skills/conceptual-blending
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Conceptual Blending in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Conceptual Blending on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Conceptual Blending is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

conceptual-blending

Purpose

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

Input contract

yaml
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

yaml
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.

Frequently asked questions

What does the Conceptual Blending AI skill do?

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.

Why use Conceptual Blending on TypingMind?

Because you install it once and use it with any model. Conceptual Blending is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Conceptual Blending in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/conceptual-blending. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Conceptual Blending?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Conceptual Blending?

As many as you like. As long as a model supports skills, you can use Conceptual Blending with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Conceptual Blending AI skill free?

Yes. It is published on GitHub by yogsoth-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Related AI Skills

View all
nexu-io logo

Html Ppt Zhangzara Monochrome

nexu-io
OrganizationPopular

A grant proposal on CRISPR base-editing for sickle-cell disease — the hypothesis, the approach, the milestones, and the risk. Built as a decision-grade academic research deck for grant review…

11.2K
96.7K
2 files
View
nexu-io logo

Html Ppt Zhangzara Scatterbrain

nexu-io
OrganizationPopular

A design-school graduation project: a civic wayfinding system for a transit hub — the brief, the process, and the outcome. Built as a decision-grade coursework defense deck for crit panel, faculty.

11.2K
96.7K
2 files
View
paperclipai logo

Create Agent Adapter

paperclipai
OrganizationPopular

Create or modify Paperclip agent adapters across server, UI, and CLI surfaces. Use when adding support for a new CLI agent, API agent, custom process, or adapter package.

16.2K
95.4K
Instructions
View
paperclipai logo

Create Paperclip Bundled Skill

paperclipai
OrganizationPopular

Turn an idea, tweet, or task into a skill in the Paperclip skills catalog (packages/skills-catalog). Use when asked to FIND or MAKE a skill and publish it as a bundled/optional catalog skill: research…

16.2K
95.4K
2 files
View

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇