# Systematic Perturbation

> Multi-axis systematic perturbation — define variation axes, perturb along each, measure degradation, construct validity envelope.

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

---


# Systematic Perturbation

Map validity by perturbing along defined axes.

## Operations

- variation-axis-definition → controlled-perturbation → validity-envelope-construction

## Available SOPs

**Subagent:** variation-axis-definition, controlled-perturbation, validity-envelope-construction
**Import:** paper-search

## Execution Guidance

Define orthogonal axes of variation (at least 3), perturb one axis at a time while holding others constant, record performance at each point, construct envelope from degradation thresholds.

## Minimum Yield

```
<HARD-GATE>
- variation axes defined: >= 3
- perturbation curves: >= 3
- validity envelope: >= 1 constructed
</HARD-GATE>
```

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## Available SOPs

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

| SOP | When to use |
| --- | --- |
| controlled-perturbation | Systematically vary parameters along defined axes, recording performance at each point to identify degradation thresholds. |
| deep-insight-paper-search | AI-powered paper summary and search. Import of literature-engine/literature-search skill. AI summary level — cite as "AI-extracted" not "paper states". |
| deep-insight-validity-envelope-construction | Combine multi-axis perturbation data into a multi-dimensional validity description with boundary conditions and interaction effects. |
| variation-axis-definition | Identify orthogonal axes along which a method's validity might vary. Ensures axes are independent, measurable, and span the relevant parameter space. |

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