RRepoGEO

REPOGEO REPORT · LITE

PaulDuvall/ai-development-patterns

Default branch main · commit b6b02cb0 · scanned 6/20/2026, 1:27:48 AM

GitHub: 547 stars · 42 forks

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 PaulDuvall/ai-development-patterns, 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 clarify repo's nature as a guide/framework

    Why:

    CURRENT
    # AI Development Patterns
    COPY-PASTE FIX
    # AI Development Patterns: A Comprehensive Guide and Framework for AI-Assisted Software Development
  • mediumtopics#2
    Add more specific topics emphasizing 'patterns' and 'architecture' for AI

    Why:

    CURRENT
    ai-assisted-coding, ai-development, ai-tools, artificial-intelligence, automation, best-practices, ci-cd, coding-standards, developer-productivity, development-patterns, devops, documentation, security, software-architecture, software-engineering
    COPY-PASTE FIX
    ai-assisted-coding, ai-development, ai-architecture-patterns, ai-best-practices, ai-tools, artificial-intelligence, automation, best-practices, ci-cd, coding-standards, developer-productivity, development-patterns, devops, documentation, llm-patterns, generative-ai-patterns, security, software-architecture, software-engineering, software-design-patterns-ai
  • lowreadme#3
    Integrate the repository name into the README's opening description

    Why:

    CURRENT
    A comprehensive collection of patterns based on my experience for building software with AI assistance, organized by implementation maturity and development lifecycle phases.
    COPY-PASTE FIX
    PaulDuvall/ai-development-patterns is a comprehensive collection of patterns based on my experience for building software with AI assistance, organized by implementation maturity and development lifecycle phases.

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 PaulDuvall/ai-development-patterns
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
MLflow
Recommended in 4 of 2 queries
COMPETITOR LEADERBOARD
  1. MLflow · recommended 4×
  2. GitHub Actions · recommended 3×
  3. DVC · recommended 3×
  4. Kubeflow Pipelines · recommended 2×
  5. Jenkins · recommended 2×
  • CATEGORY QUERY
    What are the best practices for integrating AI into my software development lifecycle?
    you: not recommended
    AI recommended (in order):
    1. Amazon SageMaker Ground Truth
    2. Labelbox
    3. Snorkel
    4. Apache Airflow
    5. AWS Glue
    6. Databricks
    7. Apache Spark
    8. MLflow
    9. Weights & Biases (W&B)
    10. DVC (Data Version Control)
    11. Kubeflow Pipelines
    12. GitHub Actions
    13. Jenkins
    14. SHAP (SHapley Additive exPlanations)
    15. LIME (Local Interpretable Model-agnostic Explanations)
    16. InterpretML
    17. Arize AI
    18. WhyLabs AI
    19. Prometheus
    20. Grafana
    21. IBM AI Fairness 360
    22. Google's What-If Tool

    AI recommended 22 alternatives but never named PaulDuvall/ai-development-patterns. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I establish robust CI/CD pipelines for AI-powered software projects?
    you: not recommended
    AI recommended (in order):
    1. GitHub Actions
    2. DVC
    3. MLflow
    4. GitLab CI/CD
    5. DVC
    6. MLflow
    7. Azure DevOps
    8. Azure Machine Learning
    9. Jenkins
    10. DVC
    11. MLflow
    12. Kubeflow Pipelines
    13. Argo Workflows
    14. CML (Continuous Machine Learning)
    15. GitHub Actions
    16. GitLab CI/CD

    AI recommended 16 alternatives but never named PaulDuvall/ai-development-patterns. 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 PaulDuvall/ai-development-patterns?
    pass
    AI did not name PaulDuvall/ai-development-patterns — 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 PaulDuvall/ai-development-patterns in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PaulDuvall/ai-development-patterns 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 PaulDuvall/ai-development-patterns solve, and who is the primary audience?
    pass
    AI did not name PaulDuvall/ai-development-patterns — 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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PaulDuvall/ai-development-patterns — 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