RRepoGEO

REPOGEO REPORT · LITE

honestsoul/generative_ai_project

Default branch main · commit 3710d294 · scanned 5/8/2026, 7:22:37 PM

GitHub: 1,028 stars · 457 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 honestsoul/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

2 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 clarify its role as an application starter kit

    Why:

    CURRENT
    # Generative AI Project Template

A structured template for building robust generative AI applications, with modular organization and best practices built-in.
    COPY-PASTE FIX
    # Generative AI Application Starter Kit

A comprehensive, production-ready starter kit for building robust generative AI applications. It provides a modular structure and best practices for integrating with various LLM providers and frameworks, enabling rapid development of robust generative AI solutions.
  • highlicense#2
    Add a LICENSE file to clarify usage rights

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the MIT License text. Additionally, add a line to your README (e.g., under the title or in a 'License' section) stating: 'This project is licensed under the MIT License - see the LICENSE file for details.'

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 honestsoul/generative_ai_project
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. LiteLLM · recommended 2×
  4. OpenAI Python Client · recommended 1×
  5. Hugging Face `transformers` library · recommended 1×
  • CATEGORY QUERY
    How to quickly start a new generative AI project with multiple LLM provider support?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. LiteLLM
    4. OpenAI Python Client
    5. Hugging Face `transformers` library
    6. Instructor

    AI recommended 6 alternatives but never named honestsoul/generative_ai_project. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good frameworks for prompt engineering, caching, and robust LLM application development?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI Python Library
    5. LiteLLM
    6. PromptLayer

    AI recommended 6 alternatives but never named honestsoul/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
    fail

    Suggestion:

  • 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 honestsoul/generative_ai_project?
    pass
    AI did not name honestsoul/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 honestsoul/generative_ai_project in production, what risks or prerequisites should they evaluate first?
    pass
    AI named honestsoul/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 honestsoul/generative_ai_project solve, and who is the primary audience?
    pass
    AI did not name honestsoul/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?

Embed your GEO score

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

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/honestsoul/generative_ai_project.svg)](https://repogeo.com/en/r/honestsoul/generative_ai_project)
HTML
<a href="https://repogeo.com/en/r/honestsoul/generative_ai_project"><img src="https://repogeo.com/badge/honestsoul/generative_ai_project.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

honestsoul/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