Registry › Compare › DSH TUI vs Notebooklm Py

DSH TUI vs Notebooklm Py

Notebooklm Py leads on trust: 89.2/100 (Grade A) against 81.7/100 (Grade A), a 7.5-point gap. DSH TUI leads on maintenance; Notebooklm Py leads on supply-chain integrity and adoption.

A DSH TUI 81.7

DSH's officially top-recommended TUI plugin — high performance, low overhead, cute pixel whale, smooth mouse interaction. One-command install via npm. / DSH 官方首推的 TUI 插件，高性能低占用，可爱像素鲸鱼，流畅鼠标交互，npm 一键安装

ccch1mneyyy/dsh-TUI · #15 overall · #15 Agent Skills · coverage B (3/5)

Choose DSH TUI if maintenance matters most.

+1.4Maintenance

A Notebooklm Py 89.2

Unofficial Python API and agentic skill for Google Gemini Notebook. Full programmatic access to NotebookLM's features—including capabilities the web UI doesn't expose—via Python, CLI, and AI agents like Claude Code, Codex, and OpenClaw.

teng-lin/notebooklm-py · #3 overall · #3 Agent Skills · coverage B (3/5)

Choose Notebooklm Py if supply-chain integrity and adoption matter most.

+3.2Safety / Integrity: 56% of recent commits signed, against 41%
+2.3Adoption: 37.9k weekly downloads against 10.4k
+1.7Transparency: OSSF Scorecard 6.3 against 4.4

Where they differ

15.0

Safety / IntegrityNotebooklm Py +3.2

18.2

12.2

TransparencyNotebooklm Py +1.7

13.9

19.9

MaintenanceDSH TUI +1.4

18.5

14.1

AdoptionNotebooklm Py +2.3

16.4

+2.5

Runtime calibrationNotebooklm Py +1.7

+4.2

1 dimension identical: Identity 18.0 · Full evidence table

An independent, evidence-based trust comparison of DSH TUI and Notebooklm Py, two Agent Skills projects in the HVTracker registry. Scores come from public, checkable signals — supply-chain provenance, OSSF Scorecard, maintenance, and adoption — not popularity.

Full evidence

Signal	DSH TUIccch1mneyyy/dsh-TUI	Notebooklm Pyteng-lin/notebooklm-py
HVTrust score	81.7	89.2
Evidence grade	A	A
Coverage grade	B	B
Overall rank	#15	#3
Rank in Agent Skills	#15	#3
GitHub stars	4.3k	19.7k
Last updated	1d ago	1d ago
Build provenance	Yes	Yes
OSSF Scorecard	4.4 / 10	6.3 / 10
License	MIT	MIT
Downloads	10k/wk	38k/wk
Trust dimensions (points earned)
Safety / integrity / 25	15.0	18.2
Identity & provenance / 18	18.0	18.0
Transparency / 17	12.2	13.9
Maintenance / 20	19.9	18.5
Adoption / 20	14.1	16.4
Runtime capability surface (full matrix)
MCP server	—	Implemented
External providers	2 — Anthropic, DeepSeek	—
Requires API keys	Yes	No
Plugin surface	—	—
Provenance drift	Match	Match

Open in the live compare tool → DSH TUI profile Notebooklm Py profile More Agent Skills →

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 v4.4 →