agentc vs Open-Source DaiDocs now beats Graphify by 218x low tokens, 83% on LME

A minimal, static, embeddable AI agent in C - no libc, less than 1MB. - GitHub - abird-ai/agentc: A minimal, static, embeddable AI agent in C - no libc, less than 1MB. Sharing an agent that I built since most of the agents that's nice to work with, take hefty deps like node or is provider dependent.It's heavily inspired by the wonderful pi agent - and builds on it as something that you can run on tiny hardware or embed easily in your own binaries without needing it's hefty dependency chain.An agent doesn't really need much - a minimal networking stack, a TUI and an agent loop. Then comes tools, mcp, skills and prompts.agentc does exactly that - a minimal, static, embeddable coding agent in C - no libc, less than 1MB, starts up using <1...

Open plain-text file format for AI memory. Your assistant's long-term memory as .dai files on your disk: readable by Claude, GPT, Gemini, Cursor, local models and grep (all LLM models work). MCP server + hooks for Claude Code, Claude Desktop, Cursor, Windsurf, Codex. 83% LongMemEval-S (GPT-4o), 92% (Claude Fable 5), 10x fewer tokens. - Kerneta/daidocs We have been working on making an Open-Source standard documents for AI LLM's and Agents. Just like an excel file, .dai (Document AI) is a new standard to keep memory local and use with any AI agents and LLM's. This new standard comes with lots of features such as more than 10x tokens savings (tested on LongMemEval-S) when comapred the .dai to raw files and scored 83% with gpt-4-0 and 92% with Fable 5! (This shows how well it remembers a very long conversation), as well as an increased context window (fitting more than 1m tokens chat in a model which has a max of 1m context window)...