Every coding-agent session trains the next models. Today that data goes to a few companies — donate yours instead, anonymized on your machine, to a dataset anyone can train on.
npx skills add trace-commons-ai/donate-trace
Then run /donate-trace after an open-source session. It anonymizes locally, shows what it removed, and sends only when you confirm.
Coding models improve on the data their makers can see. A shared, openly-licensed dataset levels that field.
A diff shows where you landed; a trace shows how you got there. That reasoning is what's locked inside a few companies today.
One openly-licensed dataset on Hugging Face anyone can download, study, and build on. It belongs to the community that fills it.
Paths, usernames, and secrets are stripped on your own machine — and you review what's left before anything sends.
One installer for every agent. No Hugging Face account needed.
Auto-detects and installs into each agent you use — Claude Code, Codex, pi, opencode, and 50+ more.
npx skills add trace-commons-ai/donate-trace
After a session on open-source work, run /donate-trace (pi: /skill:donate-trace). It confirms the repo is public first.
/donate-trace
See exactly what was removed, then confirm. It opens as a pull request a maintainer reviews before anything goes public — anonymous, or attributed if you're logged in.
One public row per donation. Watch it grow — or open the whole dataset on Hugging Face.
Open infrastructure is built, not given — one session at a time. Donate a trace and keep the next coding models open.