I tracked every GitHub traffic spike for my open source LLM proxy for 7 weeks. Then I did the exact same thing again, and it worked again.
The developer of Trooper, a privacy-aware LLM proxy written in Go, tracked every GitHub traffic spike for 7 weeks. Trooper sits between an app and an LLM provider, automatically falling back to a local Ollama instance when cloud quota runs out, with zero code changes. It also tracks session context so agents don't go blind between calls. The developer created a ranked table of spikes, with the top driver being a Reddit wave peak on May 13 (375 clones, 1,113 views), followed by a Reddit launch spike on May 10-12 (312 clones, 974 views), and a post on r/ollama titled 'Escalate the model' on Jun 10 (289 clones, 749 views). The developer notes that the same playbook that worked at launch still works when you have something new to say, and that plumbing (like Trooper) doesn't go viral the way demos do.
Developers can learn a repeatable playbook for driving GitHub traffic to open source tools.