RRepoGEO

REPOGEO REPORT · LITE

oegedijk/explainerdashboard

Default branch master · commit 678e695d · scanned 5/10/2026, 1:02:03 AM

GitHub: 2,485 stars · 345 forks

AI VISIBILITY SCORE
74 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
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 oegedijk/explainerdashboard, 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 to emphasize XAI dashboarding

    Why:

    CURRENT
    This package makes it convenient to quickly deploy a dashboard web app that explains the workings of a (scikit-learn compatible) machine learning model.
    COPY-PASTE FIX
    ExplainerDashboard is a powerful Python library for quickly building interactive web dashboards that visualize and explain the inner workings of machine learning models.
  • mediumtopics#2
    Add more specific XAI dashboarding topics

    Why:

    CURRENT
    dash, dashboard, data-scientists, explainer, inner-workings, interactive-dashboards, interactive-plots, model-predictions, permutation-importances, plotly, shap, shap-values, xai, xai-library
    COPY-PASTE FIX
    dash, dashboard, data-scientists, explainer, inner-workings, interactive-dashboards, interactive-plots, model-predictions, permutation-importances, plotly, shap, shap-values, xai, xai-library, xai-dashboards, ml-dashboards, model-explanation-dashboards
  • lowcomparison#3
    Add a 'Comparison to other tools' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison to other tools

ExplainerDashboard differentiates itself by offering a ready-to-use, interactive web dashboard that integrates a wide range of popular Explainable AI techniques into a single, user-friendly interface with minimal code, unlike pure XAI libraries or general-purpose dashboarding frameworks.

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
1 / 2
50% of queries surface oegedijk/explainerdashboard
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
SHAP
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. SHAP · recommended 1×
  2. LIME · recommended 1×
  3. InterpretML · recommended 1×
  4. ELI5 · recommended 1×
  5. Yellowbrick · recommended 1×
  • CATEGORY QUERY
    How to easily visualize and explain machine learning model predictions and inner workings?
    you: not recommended
    AI recommended (in order):
    1. SHAP
    2. LIME
    3. InterpretML
    4. ELI5
    5. Yellowbrick
    6. TensorBoard
    7. Captum

    AI recommended 7 alternatives but never named oegedijk/explainerdashboard. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good interactive tools for building explainable AI dashboards with SHAP values?
    you: #1
    AI recommended (in order):
    1. ExplainerDashboard ← you
    2. Streamlit
    3. Dash by Plotly
    4. Gradio
    5. Microsoft Azure Machine Learning (AML) Interpretability Dashboard
    6. Google Cloud AI Platform Explainable AI (XAI)
    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 oegedijk/explainerdashboard?
    pass
    AI named oegedijk/explainerdashboard explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of oegedijk/explainerdashboard. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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oegedijk/explainerdashboard — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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oegedijk/explainerdashboard — RepoGEO report