RRepoGEO

REPOGEO REPORT · LITE

yoheinakajima/instagraph

Default branch main · commit 65b179d9 · scanned 6/20/2026, 1:18:18 PM

GitHub: 3,550 stars · 283 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
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 yoheinakajima/instagraph, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    knowledge-graph, ai, nlp, text-to-graph, flask, python, visualization, graph-generation
  • highreadme#2
    Refine the README's opening paragraph to emphasize AI-powered generation

    Why:

    CURRENT
    Hello there, adventurous coder! Welcome to InstaGraph, your go-to application for converting text or URLs into insightful knowledge graphs. Curious about the relationships between entities in a complex topic? Feed the text to InstaGraph and voila! A beautiful knowledge graph is at your fingertips. See example flowcharts generated by InstaGraph here. Powered by OpenAI's GPT-3.5, this Flask application turns your text into a vividly colored graph, making it easier to visualize relationships between various entities. Enough talking—let's get started!
    COPY-PASTE FIX
    Hello there, adventurous coder! Welcome to InstaGraph, an AI-powered application that converts text or URLs into insightful knowledge graphs. Powered by OpenAI's GPT-3.5, this Flask application automatically generates vividly colored graphs, making it easier to visualize relationships between entities extracted from complex topics. See example flowcharts generated by InstaGraph here.
  • mediumhomepage#3
    Add the project homepage URL

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://instagraph.ai

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/instagraph
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
networkx/networkx
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. networkx/networkx · recommended 2×
  2. Neo4j Bloom · recommended 1×
  3. Neo4j Browser · recommended 1×
  4. Neo4j Graph Database · recommended 1×
  5. gephi/gephi · recommended 1×
  • CATEGORY QUERY
    How to visualize relationships between entities extracted from unstructured text data?
    you: not recommended
    AI recommended (in order):
    1. Neo4j Bloom
    2. Neo4j Browser
    3. Neo4j Graph Database
    4. Gephi (gephi/gephi)
    5. Cytoscape (cytoscape/cytoscape)
    6. KeyLines
    7. Linkurious Enterprise
    8. D3.js (d3/d3)
    9. NetworkX (networkx/networkx)
    10. Matplotlib (matplotlib/matplotlib)
    11. Plotly (plotly/plotly.py)
    12. yFiles

    AI recommended 12 alternatives but never named yoheinakajima/instagraph. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good libraries for turning text into a visual knowledge graph using AI?
    you: not recommended
    AI recommended (in order):
    1. GraphRAG
    2. Haystack (deepset-ai/haystack)
    3. spaCy (explosion/spaCy)
    4. NetworkX (networkx/networkx)
    5. Pyvis (WestHealth/pyvis)
    6. vis.js (visjs/vis-network)
    7. OpenNRE (thunlp/OpenNRE)
    8. Stanza (stanfordnlp/stanza)
    9. PyKEEN (pykeen/pykeen)
    10. AmpliGraph (Accenture/AmpliGraph)

    AI recommended 10 alternatives but never named yoheinakajima/instagraph. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

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