This one has a reasonably settled answer, so here it is. The pattern that distinguishes a bad batch from an exit is behaviour rather than product. A bad batch comes with communication, a reshipment offer and a batch number. An exit comes with slower replies, pressure toward less reversible payment methods, sudden discounting, and the same reassurance repeated without any new information. The product tells you less than the correspondence does.

If somebody has the primary source to hand I would rather cite it than paraphrase it.

Dr.AddMedPHL said:

The pattern that distinguishes a bad batch from an exit is behaviour rather than product.

Right, and one flattering data point from a group buy is not consistency. Consistency means separate batches, separately commissioned, over months.

Dr.EM_Chicago said:

Six orders from the same supplier over eight months, every one independently tested, and the consistency is the part worth reporting rather than any…

Can confirm the pattern Dr.EM_Chicago describes. The useful checklist is about verifiability rather than presentation. Independent test results commissioned by buyers rather than by the seller, consistency across multiple batches over time rather than one flattering report, a physical address and a company registration that resolve, batch and lot numbers on the actual labelling, and a shipping practice that matches what the material needs. Everything a good-looking website provides is cheap to fake; none of the items above are.

Happy to go further on any of that.

From the other side of the consultation, briefly.

Vendor reputation tracking for vendor vetting: I maintain a personal spreadsheet with every order I've placed — date, vendor, batch number, Janoshik result, personal efficacy assessment (1-5 scale), and any issues.

After 12 orders across 3 vendors: average purity 97.0%, zero sterility concerns, 1 shipping issues (all resolved). This data gives me confidence in my current source and documentation if issues arise.

I encourage everyone to track their orders systematically. Community data aggregation makes us all safer.