RRepoGEO

REPOGEO REPORT · LITE

robert-mcdermott/ai-knowledge-graph

Default branch main · commit 40b70197 · scanned 6/21/2026, 9:26:57 AM

GitHub: 2,311 stars · 335 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
33 /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
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 robert-mcdermott/ai-knowledge-graph, 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 paragraph to emphasize it's a complete application

    Why:

    CURRENT
    This system takes an unstructured text document, and uses an LLM of your choice to extract knowledge in the form of Subject-Predicate-Object (SPO) triplets, and visualizes the relationships as an interactive knowledge graph.
    COPY-PASTE FIX
    **AI Knowledge Graph Generator is a complete, ready-to-use application** that takes unstructured text, uses an LLM of your choice to extract Subject-Predicate-Object (SPO) triplets, and visualizes these relationships as an interactive knowledge graph. It provides an end-to-end pipeline from raw text to interactive visualization.
  • mediumreadme#2
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Libraries and Frameworks
Unlike general-purpose LLM orchestration frameworks (e.g., LangChain, LlamaIndex) or graph visualization libraries (e.g., NetworkX, Pyvis), AI Knowledge Graph Generator is a self-contained application providing a complete pipeline. It integrates these powerful components to offer a turnkey solution for generating and visualizing knowledge graphs from text, rather than requiring you to build the entire system from scratch.
  • lowabout#3
    Refine the GitHub 'About' description

    Why:

    CURRENT
    AI Powered Knowledge Graph Generator
    COPY-PASTE FIX
    End-to-end system for generating interactive knowledge graphs from unstructured text using LLMs.

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 robert-mcdermott/ai-knowledge-graph
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. Neo4j · recommended 1×
  3. streamlit/streamlit · recommended 1×
  4. plotly/dash · recommended 1×
  5. run-llama/llama_index · recommended 1×
  • CATEGORY QUERY
    What tools can I use to build an interactive knowledge graph from unstructured text using LLMs?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Neo4j
    3. Streamlit (streamlit/streamlit)
    4. Dash (plotly/dash)
    5. LlamaIndex (run-llama/llama_index)
    6. ArangoDB (ArangoDB/ArangoDB)
    7. Graphistry
    8. OpenAI API
    9. Google Gemini API
    10. Anthropic Claude API
    11. Amazon Neptune
    12. D3.js (d3/d3)
    13. Cytoscape.js (cytoscape/cytoscape.js)
    14. Haystack (deepset-ai/haystack)
    15. Grakn (Vaticle's TypeDB) (vaticle/typedb)
    16. React (facebook/react)
    17. Vue (vuejs/core)
    18. SpaCy (explosion/spaCy)
    19. NetworkX (networkx/networkx)
    20. Plotly (plotly/plotly.py)
    21. Bokeh (bokeh/bokeh)

    AI recommended 21 alternatives but never named robert-mcdermott/ai-knowledge-graph. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Python solution to extract subject-predicate-object triplets and visualize relationships.
    you: not recommended
    AI recommended (in order):
    1. spaCy
    2. Stanza
    3. NetworkX
    4. Matplotlib
    5. Plotly
    6. OpenNRE
    7. Textacy
    8. NLTK
    9. Stanford CoreNLP
    10. pycorenlp
    11. stanfordcorenlp

    AI recommended 11 alternatives but never named robert-mcdermott/ai-knowledge-graph. 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 robert-mcdermott/ai-knowledge-graph?
    pass
    AI did not name robert-mcdermott/ai-knowledge-graph — 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 robert-mcdermott/ai-knowledge-graph in production, what risks or prerequisites should they evaluate first?
    pass
    AI named robert-mcdermott/ai-knowledge-graph 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 robert-mcdermott/ai-knowledge-graph solve, and who is the primary audience?
    pass
    AI named robert-mcdermott/ai-knowledge-graph 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 robert-mcdermott/ai-knowledge-graph. 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/robert-mcdermott/ai-knowledge-graph.svg)](https://repogeo.com/en/r/robert-mcdermott/ai-knowledge-graph)
HTML
<a href="https://repogeo.com/en/r/robert-mcdermott/ai-knowledge-graph"><img src="https://repogeo.com/badge/robert-mcdermott/ai-knowledge-graph.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

robert-mcdermott/ai-knowledge-graph — 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