RRepoGEO

REPOGEO REPORT · LITE

LennysNewsletter/lennys-newsletterpodcastdata

Default branch main · commit ec2134f8 · scanned 6/5/2026, 6:57:57 PM

GitHub: 538 stars · 158 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface LennysNewsletter/lennys-newsletterpodcastdata, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    podcast-transcripts, newsletter-content, ai-friendly-markdown, dataset, ai-applications, llm-development, natural-language-processing, lenny-podcast, lenny-newsletter, product-management
  • highreadme#2
    Emphasize the dataset's utility for AI/LLM development in the README's opening

    Why:

    CURRENT
    A comprehensive archive of Lenny's Podcast transcripts and Lenny's Newsletter posts, in AI-friendly markdown, to inspire you to build something with this unique dataset.
    COPY-PASTE FIX
    This repository offers a unique, AI-friendly markdown dataset of Lenny's Podcast transcripts and Lenny's Newsletter posts, specifically curated for building AI applications, LLMs, and natural language processing projects.
  • mediumreadme#3
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    Add a section or line under 'Repo layout' or 'What is included':

## License
This repository's content is provided under the terms specified in `LICENSE.md`. Please review the file for details on usage and distribution.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface LennysNewsletter/lennys-newsletterpodcastdata
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Whisper
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Whisper · recommended 1×
  2. AssemblyAI · recommended 1×
  3. Deepgram · recommended 1×
  4. kurtmckee/feedparser · recommended 1×
  5. Substack · recommended 1×
  • CATEGORY QUERY
    Where can I find a dataset of podcast transcripts and newsletter content in markdown?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Whisper
    2. AssemblyAI
    3. Deepgram
    4. feedparser (kurtmckee/feedparser)
    5. Substack
    6. Beautiful Soup (crummy/BeautifulSoup)
    7. Puppeteer (puppeteer/puppeteer)
    8. html2text (Alir3z4/html2text)
    9. turndown (domchristie/turndown)
    10. Kaggle
    11. Hugging Face
    12. Google Dataset Search
    13. arXiv
    14. ACL Anthology

    AI recommended 14 alternatives but never named LennysNewsletter/lennys-newsletterpodcastdata. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What public text datasets are available for building AI applications or language models?
    you: not recommended
    AI recommended (in order):
    1. Common Crawl
    2. Wikipedia Dumps
    3. BookCorpus
    4. OpenWebText
    5. The Pile
    6. Reddit Submissions and Comments
    7. Gutenberg Project

    AI recommended 7 alternatives but never named LennysNewsletter/lennys-newsletterpodcastdata. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of LennysNewsletter/lennys-newsletterpodcastdata?
    pass
    AI did not name LennysNewsletter/lennys-newsletterpodcastdata — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts LennysNewsletter/lennys-newsletterpodcastdata in production, what risks or prerequisites should they evaluate first?
    pass
    AI named LennysNewsletter/lennys-newsletterpodcastdata explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo LennysNewsletter/lennys-newsletterpodcastdata solve, and who is the primary audience?
    pass
    AI did not name LennysNewsletter/lennys-newsletterpodcastdata — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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LennysNewsletter/lennys-newsletterpodcastdata — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite