/concept-blending
Fauconnier-Turner 4-space model: Generic + Input1 + Input2 → Blended
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill concept-blending --agent claude-codeHow 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
/concept-blending
Context preview
The summary Claude sees to decide when to auto-load this skill.
Fauconnier-Turner 4-space model: Generic + Input1 + Input2 → Blended
SKILL.md
concept-blending.SKILL.mdname: concept-blending
description: 'Fauconnier-Turner 4-space model: Generic + Input1 + Input2 → Blended
Space'
execution: strategy
dependencies:
sops:
- blend-completion
- blend-composition
- blend-elaboration
- combinatorial-synthesis
- generic-space-extraction
- input-space-construction
- vital-relation-mapping
tactics:
- blend-construction
- emergence-detection
Concept Blending
Fauconnier-Turner 4-space model: Generic + Input1 + Input2 → Blended Space. Produce novel concepts by selectively projecting structure from two input mental spaces into a blended space that develops emergent structure.
State Ledger
| Resource | Target | Current | % | |----------|--------|---------|---| | web-search | 25 | 0 | 0% | | web-research | 10 | 0 | 0% | | paper-overview | 30 | 0 | 0% | | paper-search | 20 | 0 | 0% | | paper-research | 10 | 0 | 0% |
HARD-GATE
Cannot exit strategy until ≥80% of each budget line is consumed OR yield targets are met with justification for remaining budget.
Available Tactics
| Tactic | Role | |--------|------| | combination-mapping | Enumerate blend dimensions and viable combinations | | blend-construction | Construct complete 4-space blends with emergent structure | | emergence-detection | Detect emergent properties in completed blends |
Available SOPs
| SOP | Role | |-----|------| | input-space-construction | Build input spaces for source concepts | | generic-space-extraction | Extract shared abstract structure | | blend-composition | Compose new connections in blended space | | blend-completion | Complete blend with background knowledge | | blend-elaboration | Run blend as mental simulation | | vital-relation-mapping | Map vital relations between concepts | | combinatorial-synthesis | Synthesize blending outputs |
Execution Guidance
1. **Select Input Concepts**: Choose two concepts with rich internal structure 2. **Build Input Spaces**: Use input-space-construction to elaborate each concept's elements, relations, and attributes 3. **Extract Generic Space**: Use generic-space-extraction to find shared abstract structure 4. **Map Vital Relations**: Use vital-relation-mapping to identify compression opportunities 5. **Compose Blend**: Use blend-composition to selectively project and create new connections 6. **Complete Blend**: Use blend-completion to recruit background knowledge 7. **Elaborate Blend**: Use blend-elaboration to run the blend as simulation and discover emergent structure
<!-- BEGIN available-tables (generated) -->
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use | | --- | --- | | blend-construction | Construct complete 4-space blends with emergent structure. Orchestrates input-space-construction → generic-space-extraction → blend-composition. | | emergence-detection | Detect and validate emergent properties from combinations. Orchestrates emergent-property-identification → blend-elaboration. |
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | blend-completion | Complete blend with background knowledge | | blend-composition | Compose new connections in blended space | | blend-elaboration | Run blend as mental simulation | | combinatorial-synthesis | Synthesize all combinatorial creativity outputs | | generic-space-extraction | Extract shared abstract structure from two input spaces | | input-space-construction | Build input spaces for two source concepts | | vital-relation-mapping | Map 15 vital relations between concepts |
<!-- END available-tables (generated) -->
Read more
name: concept-blending description: 'Fauconnier-Turner 4-space model: Generic + Input1 + Input2 → Blended Space' execution: strategy dependencies: sops: - blend-completion - blend-composition - blend-elaboration - combinatorial-synthesis - generic-space-extraction - input-space-construction - vital-relation-mapping tactics: - blend-construction - emergence-detection
Concept Blending
Fauconnier-Turner 4-space model: Generic + Input1 + Input2 → Blended Space. Produce novel concepts by selectively projecting structure from two input mental spaces into a blended space that develops emergent structure.
State Ledger
| Resource | Target | Current | % | |----------|--------|---------|---| | web-search | 25 | 0 | 0% | | web-research | 10 | 0 | 0% | | paper-overview | 30 | 0 | 0% | | paper-search | 20 | 0 | 0% | | paper-research | 10 | 0 | 0% |
HARD-GATE
Cannot exit strategy until ≥80% of each budget line is consumed OR yield targets are met with justification for remaining budget.
Available Tactics
| Tactic | Role | |--------|------| | combination-mapping | Enumerate blend dimensions and viable combinations | | blend-construction | Construct complete 4-space blends with emergent structure | | emergence-detection | Detect emergent properties in completed blends |
Available SOPs
| SOP | Role | |-----|------| | input-space-construction | Build input spaces for source concepts | | generic-space-extraction | Extract shared abstract structure | | blend-composition | Compose new connections in blended space | | blend-completion | Complete blend with background knowledge | | blend-elaboration | Run blend as mental simulation | | vital-relation-mapping | Map vital relations between concepts | | combinatorial-synthesis | Synthesize blending outputs |
Execution Guidance
1. **Select Input Concepts**: Choose two concepts with rich internal structure 2. **Build Input Spaces**: Use input-space-construction to elaborate each concept's elements, relations, and attributes 3. **Extract Generic Space**: Use generic-space-extraction to find shared abstract structure 4. **Map Vital Relations**: Use vital-relation-mapping to identify compression opportunities 5. **Compose Blend**: Use blend-composition to selectively project and create new connections 6. **Complete Blend**: Use blend-completion to recruit background knowledge 7. **Elaborate Blend**: Use blend-elaboration to run the blend as simulation and discover emergent structure
<!-- BEGIN available-tables (generated) -->
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use | | --- | --- | | blend-construction | Construct complete 4-space blends with emergent structure. Orchestrates input-space-construction → generic-space-extraction → blend-composition. | | emergence-detection | Detect and validate emergent properties from combinations. Orchestrates emergent-property-identification → blend-elaboration. |
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | blend-completion | Complete blend with background knowledge | | blend-composition | Compose new connections in blended space | | blend-elaboration | Run blend as mental simulation | | combinatorial-synthesis | Synthesize all combinatorial creativity outputs | | generic-space-extraction | Extract shared abstract structure from two input spaces | | input-space-construction | Build input spaces for two source concepts | | vital-relation-mapping | Map 15 vital relations between concepts |
<!-- END available-tables (generated) -->
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.
Repo: yogsoth-ai/de-anthropocentric-research-engine
Other skills on de-anthropocentric-research-engine.
- /formated-results
Closing skill for the research-executor, loaded as the last step of formated-specs. Summarize the design just produced into one research-result JSON fenced block in your reply. Do not execute the research.
Open skill - /formated-specs
Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply. Replaces the generic spec-writing step.
Open skill - /injection-fidelity
Loss-1 judge (codex role). Given one sample's de-identified dialogue and its PolicyCard, decide axis-by-axis whether the user-simulator enacted the card's per-axis pressure. Judge enactment of the card, never whether the research is good.
Open skill - /ladder-quality-order
Loss-2 judge (codex role). Over one topic's 6 shuffled research-design samples, pairwise-rank by quality using the D1–D5 standard. Emit the pairwise log; the harness computes the order and the ladder verdicts. Judge quality difference, never against academic standards.
Open skill - /optimization-loop
The optimizer brain for the ladder-foundry pretraining loop. Runs the two-level nested batch loop, delegates gating to gate_eval, attributes a failing batch to one weight (attribute-first), and recovers from disk after compaction. Control flow is fully scripted; only the
Open skill - /acu-nugget-recall
Tactic: Extract atomic units from one paper and score how much of a caller-supplied summary covers. Use for ACU-style binary or Nugget-style ternary recall checks; cannot run without a target summary.
Open skill