RRepoGEO

REPOGEO REPORT · LITE

ammaarreshi/Gemini-Search

Default branch main · commit 4e054902 · scanned 5/11/2026, 2:43:24 PM

GitHub: 2,068 stars · 415 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 ammaarreshi/Gemini-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
  • hightopics#1
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-search, gemini-api, perplexity-clone, fullstack, react, express, typescript, tailwindcss, google-search-api, llm-application, reference-implementation
  • highreadme#2
    Strengthen README's opening to emphasize "complete application"

    Why:

    CURRENT
    A Perplexity-style search engine powered by Google's Gemini 2.0 Flash model with grounding through Google Search. Get AI-powered answers to your questions with real-time web sources and citations.
    COPY-PASTE FIX
    A complete, open-source Perplexity-style AI search engine application, powered by Google's Gemini 2.0 Flash model with grounding through Google Search. This project provides a full reference implementation for building AI-powered answers with real-time web sources and citations.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/ammaarreshi/Gemini-Search

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 ammaarreshi/Gemini-Search
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. Faiss · recommended 2×
  4. Weaviate · recommended 2×
  5. Google Search API · recommended 1×
  • CATEGORY QUERY
    How can I implement an AI search engine providing answers with real-time web sources?
    you: not recommended
    AI recommended (in order):
    1. Google Search API
    2. SerpApi
    3. Bright Data SERP API
    4. LangChain
    5. LlamaIndex
    6. OpenAI API
    7. Anthropic Claude
    8. Google Gemini API
    9. Beautiful Soup
    10. Playwright
    11. Faiss
    12. Pinecone
    13. Weaviate

    AI recommended 13 alternatives but never named ammaarreshi/Gemini-Search. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source projects exist for building a conversational AI search with source citations?
    you: not recommended
    AI recommended (in order):
    1. Haystack (deepset/haystack)
    2. LangChain
    3. LlamaIndex
    4. Rasa
    5. OpenSearch
    6. Weaviate
    7. Faiss

    AI recommended 7 alternatives but never named ammaarreshi/Gemini-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
    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 ammaarreshi/Gemini-Search?
    pass
    AI named ammaarreshi/Gemini-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 ammaarreshi/Gemini-Search in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ammaarreshi/Gemini-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 ammaarreshi/Gemini-Search solve, and who is the primary audience?
    pass
    AI named ammaarreshi/Gemini-Search explicitly

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

Embed your GEO score

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MARKDOWN (README)
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ammaarreshi/Gemini-Search — 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