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deep-insight-validity-envelope-mapping

Research
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Map multi-dimensional validity envelopes — define variation axes, perturb systematically, measure degradation, construct boundary surface.

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I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/yogsoth-ai/de-anthropocentric-research-engine/blob/HEAD/skills/deep-insight-validity-envelope-mapping/SKILL.md

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Validity Envelope Mapping

Map the conditions under which a method remains valid.

Budget

Base SOPTarget±10% Range
web-search3027–33
web-research109–11
paper-overview4036–44
paper-search3027–33
paper-research1513–17

State Ledger

<HARD-GATE>
| SOP | Done | Target | % |
|-----|------|--------|---|
| web-search | ? | 30 | ? |
| web-research | ? | 10 | ? |
| paper-overview | ? | 40 | ? |
| paper-search | ? | 30 | ? |
| paper-research | ? | 15 | ? |
Budget Gate: OPEN/CLOSED (>=80% required to exit)
</HARD-GATE>

Available Tactics

  • systematic-perturbation

Available SOPs

Import: web-search, web-research, paper-overview, paper-search, paper-research Subagent: variation-axis-definition, controlled-perturbation, validity-envelope-construction

Execution Guidance

Define orthogonal variation axes (data size, noise level, distribution type, etc.), systematically perturb along each axis, measure performance degradation, construct multi-dimensional validity envelope.

Available Tactics

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

TacticWhen to use
systematic-perturbationMulti-axis systematic perturbation — define variation axes, perturb along each, measure degradation, construct validity envelope.

Available SOPs

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

SOPWhen to use
controlled-perturbationSystematically vary parameters along defined axes, recording performance at each point to identify degradation thresholds.
deep-insight-validity-envelope-constructionCombine multi-axis perturbation data into a multi-dimensional validity description with boundary conditions and interaction effects.
variation-axis-definitionIdentify orthogonal axes along which a method's validity might vary. Ensures axes are independent, measurable, and span the relevant parameter space.