# Minimal Change Search

> Tactic: Generate candidate changes, detect flip-points where conclusion reverses, measure fragility as distance to nearest flip.

- Skill: `yogsoth-ai/minimal-change-search` (Agent Skill)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/minimal-change-search`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/minimal-change-search/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/minimal-change-search

---


# Minimal Change Search Tactic

Find the smallest perturbation that flips the conclusion — closer flip-points mean higher fragility.

## Orchestration

1. **causal-claim-extraction** identifies the conclusion to test
2. **factor-enumeration** generates candidate change dimensions
3. **counterfactual-scenario-construction** builds scenarios with graduated changes
4. **flip-point-detection** binary-searches for the minimal change that flips
5. **fragility-measurement** computes distance from actuality to flip-point
6. Repeat for each dimension within budget
7. Report: nearest flip-point, fragility index, most vulnerable dimension

## Search Strategy

- Start with large changes (clearly flips or clearly holds)
- Binary search between hold/flip boundary
- Record the minimal change magnitude per dimension
- Fragility = 1 / (distance to nearest flip-point)

## Subagents Dispatched

- causal-claim-extraction (conclusion identification)
- factor-enumeration (dimension generation)
- counterfactual-scenario-construction (graduated scenarios)
- flip-point-detection (binary search)
- fragility-measurement (distance computation)

## Termination Conditions

- All dimensions searched within budget
- Flip-point found with distance < threshold (extremely fragile)
- No flip-point found after maximum search depth (robust)

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

## Available SOPs

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

| SOP | When to use |
| --- | --- |
| causal-claim-extraction | Extract all causal claims (X causes Y, X leads to Y, X enables Y) from an artifact, producing a structured list of cause-effect pairs. |
| counterfactual-scenario-construction | Construct precise, internally consistent counterfactual scenarios where specified factors are altered, then reason about the resulting conclusion. |
| factor-enumeration | List all key factors, conditions, and assumptions that support or enable the artifact's conclusion. |
| flip-point-detection | Find the minimal change magnitude along a dimension that causes the conclusion to flip from true to false. |
| fragility-measurement | Compute a fragility index from flip-point distances and degradation scores, summarizing how robust the conclusion is. |

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