# Facet Bisociation

> Bridge two unrelated thinking matrices via Koestler bisociation. Identify independent frames of reference and force collision to produce creative insight.

- Skill: `yogsoth-ai/facet-bisociation` (Agent Skill)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/facet-bisociation`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/facet-bisociation/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/facet-bisociation

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# Facet Bisociation

Bridge two unrelated thinking matrices via Koestler bisociation — the creative act occurs at the intersection of two self-consistent but habitually incompatible frames of reference.

## State Ledger

| Resource | Target | Current | % |
|----------|--------|---------|---|
| web-search | 30 | 0 | 0% |
| web-research | 10 | 0 | 0% |
| paper-overview | 25 | 0 | 0% |
| paper-search | 15 | 0 | 0% |
| paper-research | 5 | 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 |
|--------|------|
| analogy-extraction | Extract structural principles from each matrix |
| domain-divergence | Ensure the two matrices are genuinely unrelated |
| bridge-validation | Validate that the bisociation produces deep insight, not surface pun |

## Available SOPs

| SOP | Role |
|-----|------|
| domain-scanning | Identify candidate thinking matrices |
| abstraction-extraction | Abstract the logic of each matrix |
| bisociation-network-construction | Build the collision network between matrices |
| analogy-quality-assessment | Assess depth of the bisociative connection |
| cross-domain-synthesis | Synthesize bisociation outputs into ideas |

## Execution Guidance

1. **Select Matrix A**: Identify the problem's native frame of reference (its habitual logic)
2. **Select Matrix B**: Find a genuinely unrelated frame via domain-divergence tactic
3. **Abstract both**: Extract the operating logic of each matrix using abstraction-extraction
4. **Force collision**: Identify points where the two logics intersect or contradict
5. **Extract insight**: At each collision point, derive a novel perspective or mechanism
6. **Build network**: Use bisociation-network-construction to map all collision points
7. **Validate depth**: Use bridge-validation to confirm insights are structural, not superficial

<!-- BEGIN available-tables (generated) -->

## Available Tactics

Optional, no fixed order; the final leaf is always a sop.

| Tactic | When to use |
| --- | --- |
| bridge-validation | Validate analogy depth and transfer viability. Ensures only deep structural analogies (not surface-level similarities) proceed to transfer. |
| domain-divergence | Scan and select maximally diverse source domains. Ensures creative search covers genuinely unrelated fields with high transfer potential. |

## Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use |
| --- | --- |
| abstraction-extraction | Extract abstract principles from concrete domain cases. Strips domain-specific details to reveal transferable mechanisms. |
| bisociation-network-construction | Build multi-domain bridging concept network. Creates a network of collision points between multiple thinking matrices. |
| cross-domain-synthesis | Synthesize all cross-domain findings into a structured idea report. Integrates outputs from all strategies and SOPs. |

<!-- END available-tables (generated) -->