RRepoGEO

REPOGEO REPORT · LITE

gusye1234/nano-graphrag

Default branch main · commit acb35c06 · scanned 5/12/2026, 11:01:36 PM

GitHub: 3,840 stars · 411 forks

AI VISIBILITY SCORE
35 /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
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 gusye1234/nano-graphrag, 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
    Refine the 'About' description for clearer positioning

    Why:

    CURRENT
    A simple, easy-to-hack GraphRAG implementation
    COPY-PASTE FIX
    A simple, easy-to-hack, local-first GraphRAG implementation for developers to learn and customize.
  • mediumtopics#2
    Add more specific topics to emphasize unique differentiators

    Why:

    CURRENT
    gpt, gpt-4o, graphrag, learning-by-doing, llm, rag
    COPY-PASTE FIX
    gpt, gpt-4o, graphrag, learning-by-doing, llm, rag, python, lightweight, hackable, minimal, local-first
  • lowhomepage#3
    Add a homepage URL to complete metadata

    Why:

    COPY-PASTE FIX
    https://github.com/gusye1234/nano-graphrag

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 gusye1234/nano-graphrag
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LlamaIndex
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LlamaIndex · recommended 2×
  2. LangChain · recommended 2×
  3. Neo4j · recommended 2×
  4. NetworkX · recommended 1×
  5. Graphistry · recommended 1×
  • CATEGORY QUERY
    Looking for a lightweight and easily modifiable GraphRAG implementation for LLM development.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Neo4j
    4. NetworkX
    5. Graphistry

    AI recommended 5 alternatives but never named gusye1234/nano-graphrag. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a simpler, more hackable GraphRAG framework for custom RAG applications.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Neo4j
    4. GraphRAG
    5. Kuzu

    AI recommended 5 alternatives but never named gusye1234/nano-graphrag. 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 gusye1234/nano-graphrag?
    pass
    AI named gusye1234/nano-graphrag explicitly

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

  • If a team adopts gusye1234/nano-graphrag in production, what risks or prerequisites should they evaluate first?
    pass
    AI named gusye1234/nano-graphrag 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 gusye1234/nano-graphrag solve, and who is the primary audience?
    pass
    AI named gusye1234/nano-graphrag explicitly

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

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gusye1234/nano-graphrag — 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