RRepoGEO

REPOGEO REPORT · LITE

stardustai/dataset-viewer

Default branch main · commit 47acb506 · scanned 6/13/2026, 8:31:52 PM

GitHub: 865 stars · 55 forks

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 stardustai/dataset-viewer, 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
  • highreadme#1
    Reposition the README opening to explicitly state 'desktop application'

    Why:

    CURRENT
    A modern, high-performance dataset viewer built with Tauri, React, and TypeScript.
    COPY-PASTE FIX
    Dataset Viewer is a modern, high-performance **desktop application** built with Tauri, React, and TypeScript for efficiently exploring and visualizing massive datasets.
  • hightopics#2
    Add specific topics to clarify the repo's category

    Why:

    CURRENT
    ai, file-streaming, huggingface, s3, smb, ssh, tauri, text, vibe-coding, viewer, webdav
    COPY-PASTE FIX
    ai, file-streaming, huggingface, s3, smb, ssh, tauri, text, viewer, webdav, desktop-app, gui, data-viewer, dataset-exploration
  • highlicense#3
    Add a LICENSE file to the repository root

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root of the repository with the text of the MIT License, as implied by the README badge.

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 stardustai/dataset-viewer
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Databricks Lakehouse Platform
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Databricks Lakehouse Platform · recommended 1×
  2. Trino · recommended 1×
  3. Starburst Enterprise · recommended 1×
  4. Google Cloud BigQuery Omni · recommended 1×
  5. AWS Athena · recommended 1×
  • CATEGORY QUERY
    How to efficiently view and search massive datasets stored across multiple cloud protocols?
    you: not recommended
    AI recommended (in order):
    1. Databricks Lakehouse Platform
    2. Trino
    3. Starburst Enterprise
    4. Google Cloud BigQuery Omni
    5. AWS Athena
    6. Azure Synapse Analytics
    7. Google Cloud BigQuery
    8. Elastic Stack

    AI recommended 8 alternatives but never named stardustai/dataset-viewer. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool for previewing large archive files and various data formats directly without extraction?
    you: not recommended
    AI recommended (in order):
    1. 7-Zip
    2. WinRAR
    3. Bandizip
    4. PeaZip
    5. Total Commander

    AI recommended 5 alternatives but never named stardustai/dataset-viewer. 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 stardustai/dataset-viewer?
    pass
    AI named stardustai/dataset-viewer explicitly

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

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

    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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stardustai/dataset-viewer — 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