emaadmanzoor/stoppingagents

Optimal stopping agents powered by generative large language models

42
/ 100
Emerging

This helps professionals in roles like sales or customer service optimize when to end a conversation. It takes the ongoing conversation text as input and outputs a 'wait' or 'quit' decision, balancing the value of more information against the cost of waiting. It is designed for anyone who manages conversations where making timely decisions about continuation versus termination impacts efficiency and outcomes.

Use this if you need to make optimal, real-time decisions about when to end a conversation to maximize value or minimize cost, especially in sales or service contexts.

Not ideal if your conversations have fixed lengths, require manual human discretion for every termination, or do not involve a clear trade-off between waiting and quitting.

sales-strategy customer-service-optimization conversation-management lead-qualification contact-center-efficiency
No Package No Dependents
Maintenance 10 / 25
Adoption 3 / 25
Maturity 16 / 25
Community 13 / 25

How are scores calculated?

Stars

4

Forks

2

Language

Python

License

MIT

Last pushed

Mar 02, 2026

Commits (30d)

0

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