# Knowledge Structuring Novelty Scoring

> SOP for scoring empty cells by novelty potential — how surprising and valuable would this combination be?

- Skill: `yogsoth-ai/knowledge-structuring-novelty-scoring` (Agent Skill)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/knowledge-structuring-novelty-scoring`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/knowledge-structuring-novelty-scoring/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/knowledge-structuring-novelty-scoring

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# Novelty Scoring

Score empty cells (unexplored combinations) by their novelty potential.

## Tool

`vault_search` + CC reasoning

## Protocol

1. For each empty cell, assess:
   - Distance from nearest occupied cell (more distant = more novel)
   - Feasibility (are there physical/logical constraints?)
   - Potential impact (would this combination solve known problems?)
2. Score 0-10: novelty (0=obvious, 10=paradigm-shifting)
3. Flag top-scoring cells as priority research opportunities

## HARD-GATE

<HARD-GATE>
Must provide explicit reasoning for each score, not just a number.
</HARD-GATE>

## Yield

Returns: `{ scored: Array<{combination: string, score: number, reasoning: string}> }`