RRepoGEO

REPOGEO REPORT · LITE

EthicalML/xai

Default branch master · commit 8bc9356f · scanned 5/17/2026, 5:26:42 PM

GitHub: 1,237 stars · 185 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 EthicalML/xai, 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 ethical AI and bias mitigation

    Why:

    CURRENT
    # XAI - An eXplainability toolbox for machine learning 

XAI is a Machine Learning library that is designed with AI explainability in its core.
    COPY-PASTE FIX
    # XAI - An eXplainability toolbox for ethical machine learning, bias evaluation, and mitigation 

XAI is a Machine Learning library designed for explainability, interpretability, and the evaluation and mitigation of biases in AI models, developed by The Institute for Ethical AI & ML.
  • mediumabout#2
    Update the repository description to include its ethical AI focus

    Why:

    CURRENT
    XAI - An eXplainability toolbox for machine learning
    COPY-PASTE FIX
    XAI: An explainability toolbox for ethical machine learning, focused on bias evaluation and mitigation.
  • lowhomepage#3
    Change the homepage URL to point to the library's documentation

    Why:

    CURRENT
    https://ethical.institute/principles.html#commitment-3
    COPY-PASTE FIX
    https://ethicalml.github.io/xai/index.html

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 EthicalML/xai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
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. ELI5 · recommended 1×
  4. InterpretML · recommended 1×
  5. Yellowbrick · recommended 1×
  • CATEGORY QUERY
    How can I interpret my machine learning model's predictions and understand its decision-making process?
    you: not recommended
    AI recommended (in order):
    1. SHAP
    2. LIME
    3. ELI5
    4. InterpretML
    5. Yellowbrick
    6. Dalex
    7. Skater

    AI recommended 7 alternatives but never named EthicalML/xai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help evaluate and mitigate bias in machine learning models for ethical AI?
    you: not recommended
    AI recommended (in order):
    1. IBM AI Fairness 360 (AIF360) (IBM/AIF360)
    2. Google's What-If Tool (WIT) (tensorflow/tensorboard)
    3. Microsoft Fairlearn (fairlearn/fairlearn)
    4. Aequitas (dssg/aequitas)
    5. Amazon SageMaker Clarify
    6. Fiddler AI Explainable Monitoring

    AI recommended 6 alternatives but never named EthicalML/xai. 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 EthicalML/xai?
    pass
    AI named EthicalML/xai explicitly

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

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

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

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EthicalML/xai — 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