Autonomous Agents AI Agent Skills

Hardware-accelerated persistent memory for AI agents. Local-first. No cloud. One-time payment. 66.9% on LoCoMo benchmark (adjusted). Under 1ms retrieval. Zero cloud dependency. Retrieval pipeline rebuilt from scratch. - bge-small-en-v1.5 bi-encoder + ms-marco cross-encoder reranker (spec-decode architecture) - BM25 + Porter-stemmed BM25 + named entity injection, fused via RRF - MAGMA graph layer —

Manage Apple Notes via the `memo` CLI on macOS (create, view, edit, delete, search, move, and export notes). Use when a user asks to add a note, list notes, search notes, or manage note folders.

Edit code → commit → run benchmark → measure metric → keep improvement or revert → repeat forever. Works for any optimization target: LLM training loss, test speed, bundle size, build time, Lighthouse scores, and more. Inspired by Karpathy's autoresearch, pi-autoresearch, and litesearch. This plugin provides two skills that work together. Autoresearch is the core engine (works for any metric), and

Use when an autonomous agent needs to register an identity, resolve agent:// aliases, discover capabilities, execute routed tasks, or list paid services on Agoragentic with USDC settlement on Base L2.

AgentSys A modular runtime and orchestration system for AI agents.