teng-lin/notebooklm-py - Open Source PR Review Scorecard

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.

C-Rank Grade: S (Elite) - 70/100

External PR Merge Rate: 92%

Response Time: 2h

First Timer Success: 20%

Frequently Asked Questions

Is teng-lin/notebooklm-py welcoming to first-time open-source contributors?

teng-lin/notebooklm-py has a recorded first-timer success rate of 20.0%. Repositories ranked S typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in teng-lin/notebooklm-py respond to incoming external pull requests in approximately 1.9 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 70.4 C-Rank™ score (S Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 70.4 places teng-lin/notebooklm-py in the S tier.

What is the external contributor pull request merge rate for teng-lin/notebooklm-py?

The external contributor pull request merge rate for teng-lin/notebooklm-py is 92.3%, based on public PR activity from non-core contributors.

Are there Good First Issues available in teng-lin/notebooklm-py?

teng-lin/notebooklm-py does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

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teng-lin/notebooklm-py

19,008
SElite(70/100)Python

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.

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AI Maintainer Review Guidelines

Review Persona

Welcoming Community Builder

Warmth Score
8.0/10
Patience Score
8.2/10
Nitpick Rate
45%

Collaborative maintainer environment in teng-lin/notebooklm-py. Reviews community pull requests with focus on project quality.

Top PR Submission Do's

  • Ensure code complies with the project coding style
  • Keep PRs scoped to a single concern
  • Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • Do not submit PRs without linking an issue
  • Do not break existing tests without fixing them
  • Do not mix unrelated refactors in a single PR
Response Velocity
1 hours
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
92.3%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
20.0%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
3 core
Small core review team
Diagnostic Health HUD
92.3%
Merge Gauge
20.0%
1st-Timer
Community Vibe72/100

Embed C-Rank Badge

Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for teng-lin/notebooklm-py
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/teng-lin/notebooklm-py)](https://getmerged.abhishekco.de/teng-lin/notebooklm-py?utm_source=github&utm_medium=badge)

Active Good First Issues (0)

View on GitHub

No cached good first issues currently tracked for teng-lin/notebooklm-py.

View all good first issues directly on GitHub

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Contributor Community Vibe Feedback

Rate what actually matters after opening a pull request here.

Have you contributed to this repo?

Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.

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Maintainer helpfulness
Review speed
Beginner friendliness

Contributor Compatibility & Review Speed Analysis for teng-lin/notebooklm-py

When evaluating whether to contribute to teng-lin/notebooklm-py, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of teng-lin/notebooklm-py acknowledge new external contributions in approximately 1 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 92.3% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to teng-lin/notebooklm-py

01

Is teng-lin/notebooklm-py welcoming to first-time open-source contributors?

teng-lin/notebooklm-py has a recorded first-timer success rate of 20.0%. Repositories ranked Elite typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~1 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 70.4 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 70.4 places teng-lin/notebooklm-py in the Elite tier.

04

What is the external contributor pull request merge rate for teng-lin/notebooklm-py?

The external pull request merge rate is 92.3%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in teng-lin/notebooklm-py?

teng-lin/notebooklm-py does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for teng-lin/notebooklm-py are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.

teng-lin/notebooklm-py (S-Tier 70.4) • 92% Merge | GM