robustness-testing

Research

Test conclusion robustness via multi-model convergence — enumerate assumptions, generate alternatives, compare results, flag fragile conclusions.

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How to use this skill

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Prompt to paste

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Source SKILL.md: https://github.com/yogsoth-ai/de-anthropocentric-research-engine/blob/HEAD/skills/robustness-testing/SKILL.md

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Robustness Testing

Test whether conclusions survive across different modeling choices.

Budget

Base SOP	Target	±10% Range
web-search	20	18–22
web-research	10	9–11
paper-overview	30	27–33
paper-search	25	22–28
paper-research	15	13–17

State Ledger

<HARD-GATE>
| SOP | Done | Target | % |
|-----|------|--------|---|
| web-search | ? | 20 | ? |
| web-research | ? | 10 | ? |
| paper-overview | ? | 30 | ? |
| paper-search | ? | 25 | ? |
| paper-research | ? | 15 | ? |
Budget Gate: OPEN/CLOSED (>=80% required to exit)
</HARD-GATE>

Available Tactics

multi-model-convergence

Available SOPs

Import: web-search, web-research, paper-overview, paper-search, paper-research Subagent: assumption-enumeration, alternative-model-generation, convergence-assessment, fragility-flagging

Execution Guidance

Enumerate modeling assumptions, generate alternative models by relaxing each, compare results across alternatives, flag results that depend on specific assumptions (fragile).

Available Tactics

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

Tactic	When to use
multi-model-convergence	Wimsatt-style multi-method cross-validation — enumerate assumptions, generate alternative models, compare results, flag divergences.

Available SOPs

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

SOP	When to use
alternative-model-generation	Generate alternative model formulations by relaxing, replacing, or generalizing specific assumptions.
convergence-assessment	Compare results across multiple model variants — quantitative agreement metrics and qualitative conclusion stability.
deep-insight-assumption-enumeration	Systematically identify all assumptions in a method/model — structural, parametric, distributional, and scope assumptions.
fragility-flagging	Identify which specific assumption changes cause conclusion divergence. Rates fragility severity and plausibility of alternatives.