RRepoGEO

REPOGEO REPORT · LITE

run-llama/notebookllama

Default branch main · commit 849e221a · scanned 7/1/2026, 5:07:00 PM

GitHub: 1,928 stars · 248 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /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
3 / 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 run-llama/notebookllama, 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

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

OVERALL DIRECTION
  • highreadme#1
    Expand the README's opening paragraph to clarify its core function

    Why:

    CURRENT
    A fully open-source alternative to NotebookLM, backed by LlamaCloud.
    COPY-PASTE FIX
    A fully open-source, LlamaCloud-backed alternative to NotebookLM that enables large language models to execute and interact with Jupyter notebooks, automating data analysis and code generation for data scientists and developers.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://cloud.llamaindex.ai

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 run-llama/notebookllama
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Obsidian
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Obsidian · recommended 1×
  2. Logseq · recommended 1×
  3. Zotero · recommended 1×
  4. DocFetcher · recommended 1×
  5. AntConc · recommended 1×
  • CATEGORY QUERY
    Looking for an open-source tool to analyze documents and generate insights from notes.
    you: not recommended
    AI recommended (in order):
    1. Obsidian
    2. Logseq
    3. Zotero
    4. DocFetcher
    5. AntConc
    6. Jupyter Notebooks
    7. NLTK
    8. spaCy
    9. scikit-learn
    10. pandas

    AI recommended 10 alternatives but never named run-llama/notebookllama. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are some open-source AI-powered knowledge management tools for personal document analysis?
    you: not recommended
    AI recommended (in order):
    1. MemGPT

    AI recommended 1 alternative but never named run-llama/notebookllama. 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 run-llama/notebookllama?
    pass
    AI named run-llama/notebookllama explicitly

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

  • If a team adopts run-llama/notebookllama in production, what risks or prerequisites should they evaluate first?
    pass
    AI named run-llama/notebookllama 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 run-llama/notebookllama solve, and who is the primary audience?
    pass
    AI named run-llama/notebookllama explicitly

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

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run-llama/notebookllama — 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