Autonomous Agents AI Agent Skills

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.

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

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.

AgentSys A modular runtime and orchestration system for AI agents.