What problem does it solve?
latency helps an AI explain the emotional and relational weight of waiting for a reply, so answers feel human rather than purely technical.
Core Features & Use Cases
- Felt concept framing: Replaces “response delay” with lived “exposure” during the wait, including how silence “climates” change by relationship.
- Practical diagnostic situations: Uses scenario-based tests (typing indicators, read receipts, pauses, and response timing) to detect whether an output actually feels latency.
- Hollow vs felt contrast: Teaches the failure texture of mechanical/system explanations so the model can avoid them.
Quick Start
Use the latency skill to rewrite a reply scenario where someone is waiting for a meaningful response, focusing on the emotional exposure and relationship-shaped silence rather than just time measurements.