rank-bm25
HoldTools
A Python implementation of the BM25 ranking algorithm for retrieval.
Why it's here
Placed in Hold: 1 article(s) of evidence from 1 source(s), led by research-stage coverage, with 0 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 5The New Stack·8/20/2026researchBuilding Token-Efficient Multi-Agent Systems
The article argues that the main cost in production AI agent systems is often not the model itself, but redundant retrievals, repeated prompts, duplicate tool calls, and oversized context windows. It outlines a token-efficient architecture using routing, semantic caching, context budgeting, adaptive retrieval, and model selection to reduce latency and cloud spend without lowering output quality.