How GitPop ranks the GitHub breakouts

PopScore is a 0–100 integer combining five weighted signals: star velocity (35%),activity (25%), fork engagement (20%),noise penalty (10%), and external mentions (10%). A separate LLM pipeline writes a one-sentence AI Snapshot per project. The radar refreshes four times a day. Every input is open; every weight is documented below.

PopScore is GitPop's answer to a question GitHub itself doesn't answer: which projects are actually breaking out right now?

Raw star counts reward incumbents. GitHub Trending rewards whoever added the most stars in the last 24 hours — easily inflated by a coordinated vote, an HN front-page hit, or a Chinese star farm. The PopScore is designed to be velocity-first, fraud-resistant, and size-fair: a 100-star project that gained 50 in 7 days should rank near a 10,000-star project that gained 5,000 in the same window.

The score is an integer from 0 to 100, rounded. A score of 60+ is the radar threshold (top 50); 80+ is the danger-zone "this is blowing up" band.

PopScore = S_rate  × 0.35
         + F_rate  × 0.20
         + A_score × 0.25
         + M_score × 0.10
         + N_pen   × 0.10

Output: integer 0–100 (rounded)
              

Source: github.com/getgitpop · 32 unit tests · 100% formula coverage.

Every project on the radar gets a one-sentence TL;DR, three key features, and a 1–5 star difficulty rating. Generated by an LLM from the project's README + description + topics.

You are summarizing a GitHub project for a developer who has 5 seconds.

Inputs:
- name, full_name, description, topics, primary_language
- README (first 6k chars)
- 7-day star/fork deltas

Output JSON:
{
  "tldr":       "<= 140 chars, action verb + concrete value>",
  "features":   ["...","...","..."],   // exactly 3, <= 80 chars each
  "difficulty": 1..5,                  // 1 = "curl | bash", 5 = "PhD required"
  "category":   "framework|tool|app|lib|ai|infra|other"
}

Hard rules:
- No marketing words ("revolutionary", "powerful", "next-gen")
- No invented URLs or version numbers
- "difficulty" must reflect setup pain, not code complexity

AI Snapshots are never used to compute PopScore. They are clearly labeled on every card, and the source README is always one click away.

The noise penalty is the most-contested part of the algorithm. It's also the highest-impact — turn it off and the radar fills with "awesome-react" and "100-days-of-code".

Keyword set (d1)

Case-insensitive substring match on the project name or one-line description. Triggers a 0.8 deduction (additive).

• awesome
• tutorial
• roadmap
• interview
• learning
• cheatsheet
• course
• resources

Quality signals (d2)

Missing LICENSE or README shorter than 200 characters triggers a 0.5 deduction. The cap at 0.9 (so minimum N_pen is 10) prevents a project from being scrolled off the page entirely by double-penalty.

Why additive, not multiplicative?

Under the original multiplicative design, awesome-foo (d1=0.8) × no-license (d2=0.5) = 0.10 N_pen, crushing a useful 80-PopScore project down to 8. Additive composition caps the damage at 90% of the score, so an awesome list with great activity still ranks above a quiet, average project.

• The radar is refreshed several times per day on a fixed schedule.
• End-to-end latency: a project that breaks out mid-day usually appears in the radar within a few hours of going viral.
• Every snapshot runs the full PopScore / health / maturity pipeline, so all surfaces stay in sync.

PopScore is not:

• A code-quality measure — we don't read your source.
• A security audit — npm audit and CodeQL do that better.
• A PR-review quality measure — we count merged PRs, not their substance.
• A private-repo metric — we only see public GitHub.
• Manipulation-proof — any star-based metric is gameable. We make it expensive, not impossible.
• Real-time — there is up to a 6-hour lag between a project's star count changing and the radar reflecting it.

1. Shipped

   v1.0–v1.4 · Pop Radar + AI Snapshot + directory

   The full discovery loop: trending radar, per-project snapshots, categories, and the noise gate.

2. Shipped

   v1.5–v1.7 · Health · Maturity · Compare · Weekly Digest

   Selection and retention: honest tiers, head-to-head pages, weekly recaps, newsletter.

3. Shipped

   v1.8 · best-of-ai-tools open data repo

   A bot-maintained public ranking, auto-published weekly from live PopScore data.

4. Planned

   v1.9 · Wider world

   Full multilingual interface + downloadable dataset dumps.

5. Planned

   v2.0 · Public platform

   RESTful JSON API with OpenAPI docs, watchlist alerts, embeddable widgets.