RRepoGEO

REPOGEO REPORT · LITE

antvis/AVA

Default branch ai · commit 628949da · scanned 6/21/2026, 2:01:35 PM

GitHub: 1,493 stars · 154 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
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 antvis/AVA, 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's opening paragraph to clarify AVA's identity as an open-source developer framework.

    Why:

    CURRENT
    AVA ( Visual Analytics) is a technology framework designed for more convenient visual analytics. The first A has multiple meanings: AI native, Automated, Augmented, and VA stands for Visual Analytics. It can assist users in unstructured data loading, data processing and analysis, as well as visualization code generation.
    COPY-PASTE FIX
    AVA (AI-native Visual Analytics) is an **open-source developer framework** designed to empower engineers and data scientists to build intelligent, automated, and augmented visual analytics applications. It provides a modular architecture for unstructured data loading, processing, analysis, and **visualization code generation**, leveraging AI to transform how developers create data experiences.
  • mediumtopics#2
    Add developer-centric and open-source topics to improve categorization.

    Why:

    CURRENT
    augmented-analytics, auto-insight, chart-aigc, chart-recommendation, charts, data-visualization, insight, insight-gpt, narrative-charts, visualization
    COPY-PASTE FIX
    augmented-analytics, auto-insight, chart-aigc, chart-recommendation, charts, data-visualization, insight, insight-gpt, narrative-charts, visualization, open-source, developer-tool, javascript-library, typescript, ai-framework, code-generation
  • lowhomepage#3
    Ensure the homepage and examples prominently feature developer workflows and code.

    Why:

    COPY-PASTE FIX
    Review the homepage and documentation examples to ensure they prominently feature code snippets, API usage, and clear demonstrations of how developers integrate AVA into their applications to build AI-native visual analytics solutions.

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 antvis/AVA
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Tableau Ask Data / Tableau Pulse
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Tableau Ask Data / Tableau Pulse · recommended 1×
  2. Microsoft Power BI Q&A · recommended 1×
  3. ThoughtSpot · recommended 1×
  4. Sigma Computing · recommended 1×
  5. Looker (Google Cloud Looker Studio Pro) · recommended 1×
  • CATEGORY QUERY
    How can I generate data visualizations and insights using natural language queries?
    you: not recommended
    AI recommended (in order):
    1. Tableau Ask Data / Tableau Pulse
    2. Microsoft Power BI Q&A
    3. ThoughtSpot
    4. Sigma Computing
    5. Looker (Google Cloud Looker Studio Pro)
    6. Yellowfin BI
    7. Domo

    AI recommended 7 alternatives but never named antvis/AVA. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a framework to automate data analysis and generate visualization code with AI assistance.
    you: not recommended
    AI recommended (in order):
    1. ChatGPT Code Interpreter
    2. Google Colaboratory (Colab)
    3. Gemini
    4. ChatGPT
    5. Microsoft Power BI
    6. Copilot
    7. Tableau
    8. Einstein Discovery
    9. GPT
    10. DataRobot
    11. H2O.ai

    AI recommended 11 alternatives but never named antvis/AVA. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 antvis/AVA?
    pass
    AI named antvis/AVA explicitly

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

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

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

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antvis/AVA — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite