Auto Efficiency Learning Quip 2bit

---
name: auto-efficiency-learning-quip-2bit
description: "This work studies the post-training quantization of LLM parameters as a way to improve their runtime GAP: multi-agent orchestration: competitor signal"
auto_generated: true
created: 2026-09-16
source_insight: "Efficiency learning (QuIP#: 2-bit Quantization for LLMs): How do agents run leaner?"
status: draft
fitness_score: 0
trials: 0
wins: 0
---

# Auto Efficiency Learning Quip 2Bit

## Trigger
Use when the agent encounters: This work studies the post-training quantization of LLM parameters as a way to improve their runtime

## Verification
- [ ] The skill produces the expected output for its domain
- [ ] No errors in execution
- [ ] Insight quality: actionable and specific

## Notes
Auto-generated from internet insight (Knowledge-to-Action pipeline).
Darwin will trial this skill; it gets promoted only if it wins arena fights.