RRepoGEO

REPOGEO REPORT · LITE

microsoft/responsible-ai-toolbox

Default branch main · commit 94379f64 · scanned 6/20/2026, 2:21:40 PM

GitHub: 1,787 stars · 480 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
27 /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
1 / 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 microsoft/responsible-ai-toolbox, 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 the toolbox's unified and comprehensive nature

    Why:

    CURRENT
    # Responsible AI Toolbox
Responsible AI is an approach to assessing, developing, and deploying AI systems in a safe, trustworthy, and ethical manner, and take responsible decisions and actions.

Responsible AI Toolbox is a suite of tools providing a collection of model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems.
    COPY-PASTE FIX
    # Responsible AI Toolbox
Responsible AI Toolbox is a comprehensive, unified suite of tools designed to help developers and stakeholders build, assess, and deploy AI systems responsibly. It provides model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems, covering interpretability, fairness, error analysis, and causal decision-making in one place.
  • mediumtopics#2
    Add more specific, action-oriented topics

    Why:

    CURRENT
    data-analysis, data-science, data-visualization, error-analysis, explainability, explainable-ai, explainable-ml, fairness, fairness-ai, fairness-ml, interpretability, jupyter, machine-learning, machinelearning, ml, responsible-ai, ui, visualization, widget, widgets
    COPY-PASTE FIX
    data-analysis, data-science, data-visualization, error-analysis, explainability, explainable-ai, explainable-ml, fairness, fairness-ai, fairness-ml, interpretability, jupyter, machine-learning, machinelearning, ml, responsible-ai, ui, visualization, widget, widgets, ai-assessment, model-debugging, model-monitoring, causal-inference, ai-governance
  • lowreadme#3
    Clarify that the Toolbox contains multiple dashboards and tools

    Why:

    CURRENT
    The Toolbox consists of three repositories: 
 
| Repository| Tools Covered |
    COPY-PASTE FIX
    The Toolbox is a collection of powerful tools, including interactive dashboards and libraries, designed to provide a holistic view of your AI system's behavior. It consists of three repositories:
 
| Repository| Tools Covered |

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 microsoft/responsible-ai-toolbox
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
IBM Watson OpenScale
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. IBM Watson OpenScale · recommended 1×
  2. Microsoft Azure Machine Learning Responsible AI Dashboard · recommended 1×
  3. Google What-If Tool (WIT) · recommended 1×
  4. Aequitas · recommended 1×
  5. SHAP (SHapley Additive exPlanations) · recommended 1×
  • CATEGORY QUERY
    What tools help identify and diagnose errors in machine learning models for responsible AI?
    you: not recommended
    AI recommended (in order):
    1. IBM Watson OpenScale
    2. Microsoft Azure Machine Learning Responsible AI Dashboard
    3. Google What-If Tool (WIT)
    4. Aequitas
    5. SHAP (SHapley Additive exPlanations)
    6. LIME (Local Interpretable Model-agnostic Explanations)
    7. Fiddler AI

    AI recommended 7 alternatives but never named microsoft/responsible-ai-toolbox. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for libraries to visualize and understand AI model fairness, explainability, and interpretability.
    you: not recommended
    AI recommended (in order):
    1. Microsoft InterpretML
    2. SHAP
    3. LIME
    4. Google What-If Tool
    5. IBM AI Fairness 360
    6. Google Facets
    7. Alibi Explain

    AI recommended 7 alternatives but never named microsoft/responsible-ai-toolbox. 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 microsoft/responsible-ai-toolbox?
    pass
    AI did not name microsoft/responsible-ai-toolbox — likely talking about a different project

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

  • If a team adopts microsoft/responsible-ai-toolbox in production, what risks or prerequisites should they evaluate first?
    pass
    AI named microsoft/responsible-ai-toolbox 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 microsoft/responsible-ai-toolbox solve, and who is the primary audience?
    pass
    AI did not name microsoft/responsible-ai-toolbox — likely talking about a different project

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

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