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.
@svpino: Searching data using semantic similarity alone is flawed. Graph-aware retrieval is the way to go. The basic implementat…
Oracle AI Agent Memory 26.8 introduces graph-aware retrieval, letting agents store memories as linked records with typed relationships (supersedes, supports, contradicts) and expand search results beyond flat semantic similarity. The release also adds image-aware memory, schema upgrades, and enterprise controls.
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.