RRepoGEO

REPOGEO REPORT · LITE

supabase-community/nextjs-openai-doc-search

Default branch main · commit 50d6bb71 · scanned 6/25/2026, 4:32:59 PM

GitHub: 1,728 stars · 317 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)

3 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 supabase-community/nextjs-openai-doc-search, 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 its application as a conversational AI template

    Why:

    CURRENT
    This starter takes all the `.mdx` files in the `pages` directory and processes them to use as custom context within OpenAI Text Completion prompts.
    COPY-PASTE FIX
    This starter template provides a complete, deployable solution for building a custom ChatGPT-style documentation search or Q&A system. It processes your `.mdx` files to create a knowledge base, leveraging OpenAI for text completion and Supabase with `pgvector` for efficient semantic search.
  • mediumtopics#2
    Expand topics to include application-specific keywords

    Why:

    CURRENT
    ai, chatgpt, nextjs, openai, postgres, supabase, template, vector-search
    COPY-PASTE FIX
    ai, chatgpt, nextjs, openai, postgres, supabase, template, vector-search, q-and-a, conversational-ai, documentation-search
  • lowcomparison#3
    Add a 'Why choose this template?' or 'Comparison' section to README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, e.g., 'Why choose this template?' or 'Comparison to other tools,' explaining its focus as a complete, deployable application template using Supabase, Next.js, and OpenAI, differentiating it from general frameworks or vector databases.

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 supabase-community/nextjs-openai-doc-search
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pinecone
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Pinecone · recommended 2×
  2. weaviate/weaviate · recommended 2×
  3. langchain-ai/langchain · recommended 2×
  4. run-llama/llama_index · recommended 2×
  5. Algolia · recommended 1×
  • CATEGORY QUERY
    How to build a conversational AI search engine for my website's documentation?
    you: not recommended
    AI recommended (in order):
    1. Algolia
    2. Algolia Answers
    3. OpenAI API
    4. Pinecone
    5. Weaviate (weaviate/weaviate)
    6. Chroma (chroma-core/chroma)
    7. LangChain (langchain-ai/langchain)
    8. LlamaIndex (run-llama/llama_index)
    9. Zendesk Answer Bot
    10. Intercom Answer Bot
    11. Azure AI Search
    12. Azure OpenAI Service
    13. Google Cloud Search
    14. Vertex AI
    15. Haystack (deepset-ai/haystack)

    AI recommended 15 alternatives but never named supabase-community/nextjs-openai-doc-search. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Starter template for building an AI-powered Q&A system using custom content and vector search.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. OpenAI
    3. Hugging Face Transformers (huggingface/transformers)
    4. Chroma (chromaj-ai/chroma)
    5. Pinecone
    6. Sentence Transformers (UKPLab/sentence-transformers)
    7. LlamaIndex (run-llama/llama_index)
    8. Weaviate (weaviate/weaviate)
    9. Qdrant (qdrant/qdrant)

    AI recommended 9 alternatives but never named supabase-community/nextjs-openai-doc-search. 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 supabase-community/nextjs-openai-doc-search?
    pass
    AI named supabase-community/nextjs-openai-doc-search explicitly

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

  • If a team adopts supabase-community/nextjs-openai-doc-search in production, what risks or prerequisites should they evaluate first?
    pass
    AI named supabase-community/nextjs-openai-doc-search 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 supabase-community/nextjs-openai-doc-search solve, and who is the primary audience?
    pass
    AI did not name supabase-community/nextjs-openai-doc-search — 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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supabase-community/nextjs-openai-doc-search — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite