GitHub’s default sort order lies to you. Not intentionally, but the result is the same: popular projects appear at the top regardless of whether anyone’s maintaining them. A repository with 50,000 stars from 2019 ranks above one with 5,000 stars that shipped an update yesterday. The sorting algorithm measures historical interest, not current health.
This creates a real problem. You search for a tool, find the top result with impressive star counts, clone it, and only then discover the last commit was six months ago. Issues pile up unanswered. Pull requests go unreviewed. The community has moved on, but the star count remains frozen in time, broadcasting popularity that no longer reflects reality.
Meanwhile, actively maintained projects with smaller followings get buried on page two or three. They’re shipping regular releases, responding to issues within hours, and building healthy communities—but you’ll never find them if you sort by stars alone. That’s why we built a health scoring system that measures what matters: whether a project is being maintained.
Building a Better Signal
We started by outlining the key factors for evaluating open-source projects. Not the vanity metrics like total stars or total forks—those measure historical interest. We needed signals that indicate current project health and future viability.
Community engagement proved more nuanced than we expected. It’s not just about having a large community; it’s about having an engaged one. A project with 10,000 stars and 500 people actively watching (5% engagement) is fundamentally different from one with 10,000 stars and only 100 people actively watching (1% engagement). The first one has people paying attention. The second one has people who clicked a button once and moved on. We saw repositories like Actual with high watch-to-star ratios, indicating that people weren’t just acknowledging the project—they were actively following it. Similarly, fork ratios matter. When around 15-20% of stargazers fork your repository, they’re not just browsing; they’re building with your code.
Development activity was another area where simple metrics failed us. Counting total commits isn’t useful. What matters is how recently you committed and how frequently you’re committing now. A project that pushed code yesterday is not the same as a project that last committed three months ago, even if both have “active” in their README. We needed a way to score recency that reflected this reality. Projects like Airbyte with daily commits maintain momentum. Projects with monthly commits are still alive, but they’re in a different category entirely. And projects with no commits in 90+ days? Those needed to score significantly lower regardless of their star count.
Consistency in maintenance was trickier than we thought. Not all projects use GitHub releases. Many well-maintained projects commit regularly without tagging formal releases. We couldn’t penalize projects for not using releases, but we did want to reward projects that maintain a steady release cadence. The solution was to score both: release frequency when present, and commit consistency as a baseline. A project like AppFlowy with consistent commits but infrequent releases can still score well. A project with both frequent releases and frequent commits scores even better.
We also looked at project maturity and growth momentum. Age matters because established projects have worked out their bugs and proven their staying power, but we didn’t want to penalize new projects too heavily. A six-month-old project with daily development can be a better choice than a five-year-old project that’s gone dormant. Growth momentum—measured by the number of stars a project gains per month over its lifetime—helps identify rising projects before they reach mainstream adoption. Tools like AnythingLLM show strong momentum curves, indicating growing adoption and active development.
What the Score Actually Tells You
When you see a health score on Open Apps, you’re seeing the output of a comprehensive scoring system that weighs five components: community engagement, development activity, maintenance consistency, project maturity, and trend momentum. Each component uses nonlinear scaling—logarithmic curves for metrics such as stars and commits, and exponential decay for recency—because it better reflects reality than simple linear scoring.
A score of 85+ indicates the project has a strong, engaged community, recent commits (within the last week or two), consistent maintenance patterns, sufficient age to be stable, and a healthy growth trajectory. These are projects you can deploy in production with confidence. Activepieces typically scores in this range—daily commits, regular releases, responsive maintainers, and a growing community.
A score of 65-84 indicates a solid, well-maintained project that may have slightly lower community engagement or less frequent updates, but remains actively supported. These are great for side projects and non-critical deployments. Many mature, stable projects fall within this range because they no longer require daily updates—they’ve reached a steady state.
A score of 40-64 suggests caution. The project may be new (not yet built community or maturity) or in decline (activity is slowing). You need to investigate to determine which scenario applies manually. Sometimes you’ll find hidden gems that are brand-new yet well-engineered. Other times, you’ll find projects on their way to abandonment.
Below 40 is a red flag. Either the project is very new (less than a month old), or it’s been abandoned. Check the commit history and decide if you want to take that risk. For learning and experimentation, these can be fine. For production? Probably not.
The Weekly Recalculation
We recalculate each repository’s health score weekly. This isn’t arbitrary—it’s the cadence that balances freshness with stability. Monthly would be too slow; projects can go quiet or suddenly ramp up activity within a month. Daily would be too noisy and computationally expensive, and scores wouldn’t change meaningfully day-to-day anyway. Weekly hits the sweet spot.
This weekly recalculation means the score reflects current project status, not a snapshot from when we first indexed it. If AFFiNE ships a major release this week, the score will reflect increased activity next week. If a project goes quiet for two weeks, the score will drop. You’re always seeing recent data, which is exactly what you need when making decisions about which tools to adopt.
We’ve seen projects jump 15 points in a month after a new maintainer team took over and started shipping regular updates. We’ve also seen projects drop 20 points in six weeks as activity tapered off. The score isn’t static—it tracks the project’s actual health trajectory over time.
What We Learned
Building this system taught us things we didn’t expect. The biggest surprise was how poorly stars correlate with active maintenance. We found dozens of repositories with 30,000+ stars that hadn’t been touched in six months. We also found repositories with 2,000 stars receiving daily commits and weekly releases. Stars are a lagging indicator—they reflect past interest, not current health.
We also learned that community quality matters more than community size. A project with 5,000 stars and a 5% watch rate has a healthier community than a project with 50,000 stars and a 1% watch rate. The smaller project has 250 people actively engaged; the larger one has 500 people engaged despite being 10x larger. Per-capita engagement is a better signal than absolute numbers.
Release cadence varies wildly by project type. Backend frameworks might be released monthly. Command-line tools might be released quarterly. We had to make releases optional in the scoring system because commit consistency proved a more consistent indicator of active maintenance. Projects maintain different release philosophies, but all commit code when actively developed.
Recency matters enormously. We experimented with different scoring approaches, and exponential decay for recency gave us the best results. The difference between a commit from seven days ago and thirty days ago is significant. The difference between ninety days and 180 days is massive. Linear scoring didn’t capture that reality—exponential decay did.
Using Health Scores in Practice
We use health scores ourselves when evaluating tools for internal projects. For production deployments where reliability matters, we filter for scores above 75. That gives us actively maintained projects with strong communities and consistent development patterns. For side projects and experiments, we’ll reduce the target to 60, accepting slightly more risk in exchange for exploring newer or less popular options.
The score also helps when comparing alternatives. If you’re looking at workflow automation tools, you might see n8n with a score of 88 and another tool with a score of 62. Both may have similar features, but the health score indicates which one is currently more actively maintained. That’s valuable information when you’re making a long-term commitment to a tool.
We’ve also noticed that health scores help identify projects in transition. A formerly high-scoring project that drops to 65 might be losing maintainer support. A low-scoring project that jumps to 70 might have new maintainers bringing it back to life. These trends are useful signals that stars alone would never reveal.
The Bigger Picture
GitHub stars will always be the most visible metric because they’re simple and GitHub displays them prominently. But simple metrics create simple thinking, and open source project health isn’t simple. A comprehensive scoring system that considers community engagement quality, development recency, maintenance patterns, project maturity, and growth momentum provides a clearer picture of whether a project is worth your time.
We built this system because we kept making bad recommendations based on star counts. Now, when someone asks for a tool recommendation, we can point them to projects that aren’t just popular—they’re actively maintained, well-supported, and have healthy communities. That’s what matters when you’re choosing open source tools for production use.
The health score won’t tell you if a project is the right fit for your specific use case. It won’t tell you whether the architecture meets your needs or whether the feature set is complete. But it will tell you whether the project is alive and healthy, and whether it will be maintained when you need updates or bug fixes six months from now. That’s a question stars can’t answer, but health scores can.
Every week, we recalculate. Every week, the scores stay current. And every week, you can make better decisions about which open source projects deserve your attention.