dotnet/machinelearning vs ql-win/quicklook
dotnet/machinelearning shows stronger signals overall
As of June 2026, machinelearning shows healthier maintenance signals than quicklook. machinelearning rates Healthy overall while quicklook rates Mixed. machinelearning last saw a commit 1 month ago with 28+ active contributors, while quicklook last saw a commit 1 month ago with 4+ active contributors. machinelearning is MIT-licensed while quicklook is GPL-3.0-licensed. Neither has known critical or high-severity CVEs in its dependency tree.
Informational only. RepoPilot summarises public signals at the time of analysis. Not professional, security, or legal advice.
dotnet/machinelearning →
Healthy across the board
Permissive license, no critical CVEs, actively maintained — safe to depend on.
Has a license, tests, and CI — clean foundation to fork and modify.
Documented and popular — useful reference codebase to read through.
No critical CVEs, sane security posture — runnable as-is.
- ⚠No test directory detected
- ✓Last commit 6d ago
- ✓28+ active contributors
- ✓Distributed ownership (top contributor 21% of recent commits)
- ✓MIT licensed
- ✓CI configured
Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests
ql-win/quicklook →
Single-maintainer risk — review before adopting
copyleft license (GPL-3.0) — review compatibility; top contributor handles 94% of recent commits…
Has a license, tests, and CI — clean foundation to fork and modify.
Documented and popular — useful reference codebase to read through.
Scorecard "Branch-Protection" is 0/10; Scorecard "Token-Permissions" is 0/10
- ⚠Small team — 4 contributors active in recent commits
- ⚠Single-maintainer risk — top contributor 94% of recent commits
- ⚠GPL-3.0 is copyleft — check downstream compatibility
- ⚠No test directory detected
- ⚠Scorecard: default branch unprotected (0/10)
- ✓Last commit 2d ago
- ✓4 active contributors
- ✓GPL-3.0 licensed
- ✓CI configured
What would improve this?
- →Use as dependency Concerns → Mixed if: relicense under MIT/Apache-2.0 (rare for established libs)
- →Deploy as-is Mixed → Healthy if: bring "Branch-Protection" to ≥3/10 (see scorecard report)
Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests, cross-checked against OpenSSF Scorecard
Signal-by-signal breakdown
| machinelearning | quicklook | |
|---|---|---|
| Stars | 9,330 | 23,409 |
| Last commit | 1mo ago | 1mo ago |
| License | MIT | GPL-3.0 |
| Open issues | 999 | 173 |
| Has tests | — | — |
| Has CI | ✓ | ✓ |
| Test coverage | 0% | 0% |
| Dependency CVEs | No CVEs | No CVEs |
| Architecture grade | — | C |
| Cycles | — | 0 |
| Bottom-line | Healthy signals | Mixed signals |
Want the full analysis? dotnet/machinelearning · ql-win/quicklook
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