AI audit vs rubric — Megagoods
An independent Workers AI LLM scored Megagoods against the same published rubric. The deterministic rubric result is our canonical score. The LLM's result is shown here as a sanity check — never mixed into the scoring formula.
| Dimension | Rubric | LLM | Δ (LLM − Rubric) |
|---|---|---|---|
| Pricing transparency | 84 | 20 | -64 |
| Business transparency | 40 | 25 | -15 |
| Shipping clarity | 92 | 85 | -7 |
| Public reviews | 72 | 0 | -72 |
| Product range | 45 | 0 | -45 |
| Access & onboarding | 65 | 40 | -25 |
| Support track record | 68 | 0 | -68 |
| Store integrations | 25 | 0 | -25 |
| Overall | 65 | 15 | -50 |
What this means: Large disagreement — investigate. The LLM read the published signals very differently from the deterministic rules.
Median per-dimension |Δ| = 35.
Megagoods has opaque pricing, no public business information, and poor review scores. The platform has a small product range and no native integrations.This is the LLM's own explanation, not editorial commentary from SupplierSpy. The LLM result is a sanity check on the rubric — never mixed into the scoring formula.