RRepoGEO

REPOGEO REPORT · LITE

HeyNina101/generative_ai_project

Default branch main · commit 294c4636 · scanned 6/10/2026, 4:08:18 AM

GitHub: 899 stars · 271 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 HeyNina101/generative_ai_project, 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 H1 and opening paragraph to explicitly state its purpose as a template for new projects

    Why:

    CURRENT
    # 🧠 Generative AI Project Template

A production-ready template to help you kickstart and organize your Generative AI projects with clarity and scalability in mind. Designed to reduce chaos in early development and support long-term maintainability with proven structure and practices.
    COPY-PASTE FIX
    # 🧠 Generative AI Project Template: Production-Ready Structure for New Projects

This repository provides a production-ready template to help you kickstart and organize *new* Generative AI projects with clarity and scalability in mind. It's designed to reduce chaos in early development and support long-term maintainability with proven structure and practices, rather than serving as a general learning resource or collection of examples.
  • mediumhomepage#2
    Update the 'Homepage' field to a project-specific URL

    Why:

    CURRENT
    https://www.linkedin.com/in/ninadurann/
    COPY-PASTE FIX
    Update the 'Homepage' field to a project-specific URL (e.g., a GitHub Pages site, a dedicated project page, or a link to more extensive documentation within the repo) that clearly represents the Generative AI Project Template itself, rather than a personal profile.
  • lowtopics#3
    Add more specific topics to reinforce the repo's identity

    Why:

    CURRENT
    ai-projects, ai-template, generative-ai, llm, prompt-engineering, template
    COPY-PASTE FIX
    ai-projects, ai-template, generative-ai, llm, prompt-engineering, template, production-ready-ai, scalable-llm-apps, llm-architecture, project-structure

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 HeyNina101/generative_ai_project
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
gradio-app/gradio
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. gradio-app/gradio · recommended 2×
  2. run-llama/llama_index · recommended 2×
  3. langchain-ai/langchain-templates · recommended 1×
  4. Vercel · recommended 1×
  5. Hugging Face Spaces Templates · recommended 1×
  • CATEGORY QUERY
    How to quickly start a new scalable generative AI application with a structured template?
    you: not recommended
    AI recommended (in order):
    1. LangChain Templates (langchain-ai/langchain-templates)
    2. Vercel
    3. Gradio (gradio-app/gradio)
    4. LlamaIndex Starter Templates (run-llama/llama_index)
    5. Hugging Face Spaces Templates
    6. Cookiecutter Data Science (drivendata/cookiecutter-data-science)
    7. Cookiecutter (cookiecutter/cookiecutter)
    8. Streamlit (streamlit/streamlit)
    9. Gradio (gradio-app/gradio)
    10. OpenAI's API
    11. Anthropic's Claude
    12. transformers (huggingface/transformers)

    AI recommended 12 alternatives but never named HeyNina101/generative_ai_project. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are best practices for building maintainable and production-ready LLM applications?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. MLflow (mlflow/mlflow)
    5. Weights & Biases (W&B) (wandb/wandb)
    6. FastAPI (tiangolo/fastapi)
    7. Kubernetes (kubernetes/kubernetes)
    8. Hugging Face Inference Endpoints
    9. Prometheus (prometheus/prometheus)
    10. Grafana (grafana/grafana)
    11. OpenTelemetry (open-telemetry/opentelemetry-python)
    12. LangSmith
    13. Git (git/git)
    14. GitHub Actions
    15. GitLab CI/CD
    16. Jenkins (jenkinsci/jenkins)

    AI recommended 16 alternatives but never named HeyNina101/generative_ai_project. 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 HeyNina101/generative_ai_project?
    pass
    AI did not name HeyNina101/generative_ai_project — 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 HeyNina101/generative_ai_project in production, what risks or prerequisites should they evaluate first?
    pass
    AI named HeyNina101/generative_ai_project 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 HeyNina101/generative_ai_project solve, and who is the primary audience?
    pass
    AI did not name HeyNina101/generative_ai_project — 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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HeyNina101/generative_ai_project — 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