RRepoGEO

REPOGEO REPORT · LITE

RootbeerComputer/backend-GPT

Default branch main · commit e1cd4c0c · scanned 5/10/2026, 7:42:56 PM

GitHub: 2,935 stars · 221 forks

AI VISIBILITY SCORE
23 /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
2 / 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 RootbeerComputer/backend-GPT, 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
  • highabout#1
    Add a concise 'About' description

    Why:

    COPY-PASTE FIX
    An entire backend and database powered purely by an LLM, inferring business logic from API calls and persisting state without traditional code or databases.
  • hightopics#2
    Add specific topics for LLM-driven backends

    Why:

    COPY-PASTE FIX
    llm-backend, generative-ai, serverless, api-gateway, database, business-logic, ai-driven-development, backend-as-a-service
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).

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 RootbeerComputer/backend-GPT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
FastAPI
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. FastAPI · recommended 1×
  2. TensorFlow · recommended 1×
  3. PyTorch · recommended 1×
  4. scikit-learn · recommended 1×
  5. Flask · recommended 1×
  • CATEGORY QUERY
    What tools allow me to build backend APIs with AI-inferred business logic?
    you: not recommended
    AI recommended (in order):
    1. FastAPI
    2. TensorFlow
    3. PyTorch
    4. scikit-learn
    5. Flask
    6. Node.js
    7. Express.js
    8. TensorFlow.js
    9. Google Cloud AI Platform
    10. AWS SageMaker
    11. Azure Machine Learning
    12. Java
    13. Spring Boot
    14. Deeplearning4j
    15. Go
    16. Gin Gonic
    17. Echo
    18. ONNX Runtime
    19. Microsoft .NET
    20. ASP.NET Core
    21. ML.NET

    AI recommended 21 alternatives but never named RootbeerComputer/backend-GPT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I create a persistent backend and database purely driven by an LLM?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. PostgreSQL
    4. MongoDB
    5. Cassandra
    6. OpenAI API
    7. Microsoft Azure OpenAI Service
    8. Google Cloud Vertex AI
    9. Azure SQL Database
    10. Cosmos DB
    11. Cloud SQL
    12. Firestore
    13. Chroma
    14. Pinecone
    15. Weaviate
    16. S3
    17. Google Cloud Storage

    AI recommended 17 alternatives but never named RootbeerComputer/backend-GPT. 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 RootbeerComputer/backend-GPT?
    pass
    AI did not name RootbeerComputer/backend-GPT — 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 RootbeerComputer/backend-GPT in production, what risks or prerequisites should they evaluate first?
    pass
    AI named RootbeerComputer/backend-GPT 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 RootbeerComputer/backend-GPT solve, and who is the primary audience?
    pass
    AI named RootbeerComputer/backend-GPT explicitly

    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 RootbeerComputer/backend-GPT. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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