RRepoGEO

REPOGEO REPORT · LITE

neo4j-labs/create-context-graph

Default branch main · commit 719478a2 · scanned 5/24/2026, 4:58:21 PM

GitHub: 602 stars · 82 forks

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 neo4j-labs/create-context-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 sentence to clearly state its function as an application generator

    Why:

    CURRENT
    Interactive CLI scaffolding tool that generates fully-functional, domain-specific context graph applications.
    COPY-PASTE FIX
    Create Context Graph is an interactive CLI tool that rapidly generates complete, full-stack AI agent applications with graph-based reasoning memory, tailored to your domain.
  • hightopics#2
    Expand repository topics to include broader categories related to AI agent development and application generation

    Why:

    CURRENT
    agent-memory, context-graph, neo4j
    COPY-PASTE FIX
    ai-agents, llm-applications, scaffolding, cli-tool, full-stack, rag, agent-memory, context-graph, neo4j
  • mediumabout#3
    Refine the repository description to explicitly state its function as a generator of AI agent applications

    Why:

    CURRENT
    AI agents with graph based reasoning memory, scaffolded in seconds
    COPY-PASTE FIX
    Generate full-stack AI agent applications with graph-based reasoning memory, scaffolded in seconds.

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 neo4j-labs/create-context-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/neo4j · recommended 1×
  3. run-llama/llama_index · recommended 1×
  4. microsoft/GraphRAG · recommended 1×
  5. Azure Cosmos DB for Apache Gremlin · recommended 1×
  • CATEGORY QUERY
    How to quickly scaffold an AI agent application with graph-based reasoning memory?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Neo4j (neo4j/neo4j)
    3. LlamaIndex (run-llama/llama_index)
    4. GraphRAG (microsoft/GraphRAG)
    5. Azure Cosmos DB for Apache Gremlin
    6. Marvin (prefect-ai/marvin)
    7. NetworkX (networkx/networkx)
    8. ArangoDB (arangodb/arangodb)
    9. Dgraph (dgraph-io/dgraph)

    AI recommended 9 alternatives but never named neo4j-labs/create-context-graph. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool to generate full-stack domain-specific AI agent applications with conversational memory?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. FastAPI
    3. Streamlit
    4. LlamaIndex
    5. Flask
    6. React
    7. Microsoft Semantic Kernel
    8. ASP.NET Core
    9. Blazor
    10. OpenAI Assistants API
    11. Next.js
    12. Vercel
    13. Haystack
    14. Django
    15. Vue.js
    16. Cortex
    17. Botpress

    AI recommended 17 alternatives but never named neo4j-labs/create-context-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 neo4j-labs/create-context-graph?
    pass
    AI named neo4j-labs/create-context-graph explicitly

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

  • If a team adopts neo4j-labs/create-context-graph in production, what risks or prerequisites should they evaluate first?
    pass
    AI named neo4j-labs/create-context-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 neo4j-labs/create-context-graph solve, and who is the primary audience?
    pass
    AI did not name neo4j-labs/create-context-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?

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  • Brand-free category queries5 vs 2 in Lite
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