These are the thresholds the agent checks every lot against. Tune them to your operation; refine them over time as real results teach you. The agent surfaces and suggests against these rules — you always decide.
⚠️ Your settings save in this browser (prototype). The real multi-user version stores them on the server. Illustrative defaults grounded in stocker best practice — tune to your operation.
The four master rules of the stocker business: 1) buy them right · 2) keep them alive · 3) help them grow · 4) sell them better than you bought. (University of Tennessee Beef.) Every rule below serves one of these.
Buy right
Minimum profit buffer
Don't approve a buy unless projected margin clears this. Setting a floor you won't go below is a named best-practice risk strategy (Progressive Cattle).
Min projected profit to approve a buy$75/head
Below this, the agent flags the buy as too thin.
Help them grow
Gain targets
The benchmark every lot's weekly weigh-in is measured against. K-State survey: typical operation targets ~1.9 ADG over 141 days; grazing runs higher.
Target ADG (lb/day)2.6 lb/day
Drylot ~2.0, good grazing ~2.5–2.6.
Slow-gain flag: % below target that trips it12%
A lot gaining more than this far below target fires SLOW_GAIN.
Keep them alive
Health thresholds
Death loss and sickness are the manageable killers. A 1% death loss on $1,800 calves adds ~$18/head the survivors must cover (Feedlot Magazine).
Death loss alert (%)2.0%
Death rate above this fires DEATH_SPIKE.
Sickness alert (%)4.0%
Morbidity above this fires SICKNESS.
Sell better
Sell & hedge triggers
When the lockable futures price beats breakeven, that's a real profit to lock. Value of gain only holds if the output price is locked at purchase (UT Beef).
Sell/lock trigger: $/lb futures over breakeven$0.05/lb
Futures this far over breakeven fires MARKET_CROSS — lock it.
Restock prompt: days since buy160 days
Pen open this long prompts a replacement buy (double-checked).
Adjust rules, then save.
Built by Monte Fisher, CPA (Ret.), CFE · a Fisher Governance forensic model · private · illustrative data