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 | 11 | -54 |
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, with no source prices visible. Business transparency is low, with a private company and no audited statements. Review score is unknown. Product range is small, with an estimated 3,000 SKUs. Access is restricted, requiring signup to browse. Support reputation is unknown. Integration is manual/API only.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.