RRepoGEO

REPOGEO REPORT · LITE

supermemoryai/opensearch-ai

Default branch main · commit 3d8c34a9 · scanned 5/11/2026, 5:07:57 PM

GitHub: 1,320 stars · 201 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 supermemoryai/opensearch-ai, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    (Choose and add a standard open-source license file, e.g., MIT, Apache-2.0, GPL-3.0, to the repository root.)
  • highreadme#2
    Reposition the README H1 to explicitly state the project's purpose

    Why:

    CURRENT
    ## OpenSearch GPT
    COPY-PASTE FIX
    ## OpenSearch GPT: A Personalized AI Search Engine

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 supermemoryai/opensearch-ai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Elasticsearch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Elasticsearch · recommended 2×
  2. Apache Flink · recommended 1×
  3. Apache Kafka · recommended 1×
  4. Scikit-learn · recommended 1×
  5. TensorFlow · recommended 1×
  • CATEGORY QUERY
    How to build a personalized AI search engine that learns user interests?
    you: not recommended
    AI recommended (in order):
    1. Elasticsearch
    2. Apache Flink
    3. Apache Kafka
    4. Scikit-learn
    5. TensorFlow
    6. PyTorch
    7. Faiss
    8. Hnswlib
    9. Jupyter Notebooks
    10. Google Colab
    11. Apache Cassandra
    12. MongoDB

    AI recommended 12 alternatives but never named supermemoryai/opensearch-ai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks enable creating a custom AI search application with memory features?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. Rasa
    5. OpenAI API
    6. Anthropic's Claude
    7. Pinecone
    8. Weaviate
    9. Qdrant
    10. Elasticsearch

    AI recommended 10 alternatives but never named supermemoryai/opensearch-ai. 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 supermemoryai/opensearch-ai?
    pass
    AI named supermemoryai/opensearch-ai explicitly

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

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

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

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MARKDOWN (README)
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HTML
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