Notebooklm Py vs Waza
An independent, evidence-based trust comparison of Notebooklm Py and Waza, two Agent Skills projects in the HVTracker registry. Scores come from public, checkable signals — supply-chain provenance, OSSF Scorecard, maintenance, and adoption — not popularity.
Notebooklm Py leads on trust — 78.6/100 (Grade B) vs 77.0/100 (Grade B), a 1.6-point gap. Full breakdown below.
| Signal | Notebooklm Pyteng-lin/notebooklm-py | Wazatw93/Waza |
|---|---|---|
| HVTrust score | 78.6 | 77.0 |
| Evidence grade | B | B |
| Coverage grade | B | B |
| Overall rank | #6 | #7 |
| Rank in Agent Skills | #6 | #7 |
| GitHub stars | 19.0k | 6.9k |
| Last updated | 1d ago | 1d ago |
| Build provenance | Yes | Yes |
| OSSF Scorecard | — | 4.0 / 10 |
| License | MIT | MIT |
| Downloads | 37k/wk | 265/wk |
| Trust dimensions (points earned) | ||
| Safety / integrity / 25 | 10.1 | 12.8 |
| Identity & provenance / 18 | 18.0 | 18.0 |
| Transparency / 17 | 8.5 | 11.9 |
| Maintenance / 20 | 19.9 | 18.1 |
| Adoption / 20 | 16.4 | 12.5 |
| Runtime capability surface (full matrix) | ||
| MCP server | Implemented | — |
| External providers | — | — |
| Requires API keys | No | No |
| Plugin surface | — | plugins |
| Provenance drift | Match | Match |
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption, scaled by an evidence-confidence factor. Grade bands: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Signals refresh daily. Full methodology v4.3 →