Linking to a github repo for a binary release (no source code related to the agent that I could see) is a bit iffy IMO. You should clarify your intentions or link to something else. Might confuse folks.
https://github.com/smol-env/smol
here are traces from an agentic task around using duckduckdb
comparing CPU and RAM usage of the whole container over time w/ OpenCode, hermes, pi, codex, smol
https://x.com/__tosh/status/2086882367126286466
https://x.com/__tosh/status/2086882204060160350
smol is very minimal only using stdlib (in this case it is the go version but you can also take a look at implementations in python, clojure, php)
(any OpenAI Responses API compatible endpoint works, if your endpoint does not support 'custom' tools you can have your agent change the smol implementation to use 'function' tool implementation instead)
that said: be aware that smol does not come with any system prompt and does not load agents.md files by default
some older not so strong models benefit from a system prompt and guidance in agents.md that complements them
that said 2: system prompt and or loading agents.md automatically is easy to add though if you want it
This is a coding agent implementation I am working on, which delivers what this promises (at least on the "lean" part), except it's actually fully open source, and even more lean (few MBs of runtime memory usage).
MIT-licensed, written in C, multi-provider / multi-model, minimalist approach to system prompt and tools (think kinda like pi, but with a bit more "batteries included", like subagents and background tasks out of the box), polished presentation, inspectable (usable transcript view), etc.
Also, security aside, engineers want the freedom to modify and experiment with the tools we rely on.
Tools like this are too important to be closed. Do you want to be Internet Explorer or Firefox?
How do you think the backdoor situation would have been resolved if xz hadn't been open-source?