GitHub Archive scan of the last 30 days. Real signal, not vanity stars.
Scans 30 days of real GitHub Archive data. Results cached 24h.
We run a targeted query against the GitHub Archive public dataset — 30 days of events for your specific repo.
Pull requests and forks are weighted higher than stars. We separate evaluation signals from passive awareness signals.
Score reflects how actively developers are evaluating and contributing — not just passive interest. Dead repos score near 0.
Strong external contributor activity. Multiple developers forking, opening PRs, and filing issues. Your repo is being seriously evaluated.
Growing interest. Some external contributors and a healthy issue queue. Good foundation — developers are paying attention.
Mostly passive signals (stars, watches). Little to no external contribution activity in the last 30 days.
We query the GitHub Archive public dataset on Google BigQuery — a record of all public GitHub events going back to 2011. We look at the last 30 days for your specific repo.
The score weights intent signals: external contributors (PRs from non-team members) count 50%, issue health 30%, and fork momentum 20%. Stars are the weakest signal because they require the least commitment. Bots are filtered out.
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Results are cached for 24 hours per repo. GitHub Archive data typically has a 1–2 day lag from real-time events. For the intent score, 24h freshness is more than enough for strategic decisions.
GitHub Archive only includes public events. Private repos will return no data. Archived repos will show historical activity but likely a low score due to inactivity.