RRepoGEO

REPOGEO REPORT · LITE

gabrielchua/RAGxplorer

Default branch main · commit 840d16ab · scanned 5/18/2026, 8:42:16 AM

GitHub: 1,219 stars · 115 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 gabrielchua/RAGxplorer, 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 README H1 to emphasize RAG debugging

    Why:

    CURRENT
    RAGxplorer is a tool to build Retrieval Augmented Generation (RAG) visualisations.
    COPY-PASTE FIX
    RAGxplorer is an open-source tool for interactive visual debugging and exploration of Retrieval Augmented Generation (RAG) pipelines.
  • highabout#2
    Add homepage URL to repo About section

    Why:

    COPY-PASTE FIX
    https://ragxplorer.streamlit.app/
  • mediumtopics#3
    Add more specific RAG debugging/observability topics

    Why:

    CURRENT
    interactive, llm, python, rag, streamlit, visualization
    COPY-PASTE FIX
    interactive, llm, python, rag, streamlit, visualization, debugging, observability, rag-observability, rag-debugging

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 gabrielchua/RAGxplorer
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangSmith
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangSmith · recommended 2×
  2. explosion/spaCy · recommended 2×
  3. LlamaIndex Observability · recommended 1×
  4. Haystack UI · recommended 1×
  5. Deepset Cloud · recommended 1×
  • CATEGORY QUERY
    How can I visually debug and understand the document retrieval process in my RAG application?
    you: not recommended
    AI recommended (in order):
    1. LangSmith
    2. LlamaIndex Observability
    3. Haystack UI
    4. Deepset Cloud
    5. Weights & Biases Prompts
    6. OpenReel
    7. Streamlit
    8. Gradio

    AI recommended 8 alternatives but never named gabrielchua/RAGxplorer. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good open-source Python tools for interactively visualizing Retrieval Augmented Generation systems?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex (run-llama/llama_index)
    2. LangChain (langchain-ai/langchain)
    3. LangSmith
    4. Streamlit (streamlit/streamlit)
    5. Gradio (gradio-app/gradio)
    6. Haystack (deepset-ai/haystack)
    7. spaCy (explosion/spaCy)
    8. displaCy (explosion/spaCy)
    9. Plotly (plotly/plotly.py)
    10. Matplotlib (matplotlib/matplotlib)
    11. Seaborn (mwaskom/seaborn)

    AI recommended 11 alternatives but never named gabrielchua/RAGxplorer. 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 gabrielchua/RAGxplorer?
    pass
    AI named gabrielchua/RAGxplorer explicitly

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

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

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

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MARKDOWN (README)
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gabrielchua/RAGxplorer — 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