Reference
Summary
Reference is a local semantic search tool designed for AI agents, enabling them to retrieve relevant information locally.
Similar Articles
I built a tiny local librarian for AI agents after watching them search my repo like a raccoon in a kitchen
The author built a local search plugin called baoer_signal_grep to help AI agents navigate and search repositories more efficiently, reducing wasted time and improving multi-step investigations.
Would agents use a website's own semantic search endpoint?
The article discusses a prototype open-source package called Agentize that exposes semantic search endpoints for AI agents on websites, and questions whether this approach solves retrieval problems or duplicates existing methods.
Agent Context
Agent Context is a dev tool that lets users attach reference projects to AI coding assistants.
Search, Inspect, Fetch: Exploiting Boolean Retrieval for Deep-Research Agents
This paper introduces SIEVE, a search-inspect-fetch strategy that uses Boolean Query Language to make deep-research agents retrieve only relevant document sections, achieving higher accuracy with 20.7–50.6% fewer tokens across multiple benchmark datasets and agent backbones.
Beyond Semantic Similarity: Rethinking Retrieval for Agentic Search via Direct Corpus Interaction
The paper introduces Direct Corpus Interaction (DCI), a novel approach allowing AI agents to query raw text directly using standard terminal tools instead of traditional embedding-based retrieval. By bypassing fixed similarity interfaces and offline indexing, DCI significantly outperforms conventional sparse, dense, and reranking baselines across multiple IR and agentic search benchmarks.