RRepoGEO

REPOGEO REPORT · LITE

yoheinakajima/mindgraph

Default branch main · commit 7225b52a · scanned 5/31/2026, 5:47:45 PM

GitHub: 939 stars · 112 forks

AI VISIBILITY SCORE
30 /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
3 / 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 yoheinakajima/mindgraph, 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 statement to clarify core purpose

    Why:

    CURRENT
    Welcome to MindGraph, a proof of concept, open-source, API-first graph-based project designed for natural language interactions (input and output). This prototype serves as a template for building and customizing your own CRM solutions with a focus on ease of integration and extendibility.
    COPY-PASTE FIX
    Welcome to MindGraph, a proof of concept, open-source, API-first project for generating and querying against an ever-expanding knowledge graph with AI, designed for natural language interactions (input and output). This prototype serves as a template for building and customizing AI-powered knowledge bases, including potential applications for CRM solutions, with a focus on ease of integration and extendibility.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai, knowledge-graph, llm, natural-language-processing, python, prototype, api-first, knowledge-base
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Add a LICENSE file to the repository root, choosing a standard open-source license such as MIT or Apache-2.0.

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 yoheinakajima/mindgraph
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
django/django
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. django/django · recommended 2×
  2. Neo4j AuraDB · recommended 1×
  3. Neo4j Enterprise · recommended 1×
  4. Neo4j Bloom · recommended 1×
  5. Neo4j Browser · recommended 1×
  • CATEGORY QUERY
    How to build an AI-powered knowledge graph that supports natural language querying?
    you: not recommended
    AI recommended (in order):
    1. Neo4j AuraDB
    2. Neo4j Enterprise
    3. Neo4j Bloom
    4. Neo4j Browser
    5. GDS Library
    6. Grakn
    7. Vaticle's TypeDB
    8. Amazon Neptune
    9. Google Cloud Natural Language API
    10. BigQuery
    11. Dataproc
    12. Apache Spark GraphX
    13. Stardog
    14. Apache Jena
    15. RDF4J
    16. Virtuoso
    17. Blazegraph
    18. spaCy (explosion/spaCy)
    19. Hugging Face Transformers (huggingface/transformers)
    20. NLTK (nltk/nltk)

    AI recommended 20 alternatives but never named yoheinakajima/mindgraph. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Open-source Python frameworks for creating a dynamic, API-first knowledge base?
    you: not recommended
    AI recommended (in order):
    1. Django REST Framework (encode/django-rest-framework)
    2. Django (django/django)
    3. FastAPI (tiangolo/fastapi)
    4. Flask (pallets/flask)
    5. Flask-RESTful (flask-restful/flask-restful)
    6. Flask-RESTX (python-restx/flask-restx)
    7. Django (django/django)
    8. Sanic (sanic-org/sanic)

    AI recommended 8 alternatives but never named yoheinakajima/mindgraph. 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 yoheinakajima/mindgraph?
    pass
    AI named yoheinakajima/mindgraph explicitly

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

  • If a team adopts yoheinakajima/mindgraph in production, what risks or prerequisites should they evaluate first?
    pass
    AI named yoheinakajima/mindgraph 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 yoheinakajima/mindgraph solve, and who is the primary audience?
    pass
    AI named yoheinakajima/mindgraph explicitly

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

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yoheinakajima/mindgraph — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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