RRepoGEO

REPOGEO REPORT · LITE

neonwatty/meme-search

Default branch main · commit 876726c4 · scanned 6/4/2026, 3:57:18 AM

GitHub: 676 stars · 26 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 neonwatty/meme-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 clarify its application nature

    Why:

    CURRENT
    Use AI to index your memes by their content and text, making them easily retrievable for your meme warfare pleasures.
    COPY-PASTE FIX
    Meme Search Engine is a complete, self-hosted application for organizing and retrieving your personal meme collection using AI-powered semantic search. It's built for meme enthusiasts and content creators to easily find specific memes by content and text.
  • hightopics#2
    Add specific topics to clarify its domain and application type

    Why:

    CURRENT
    ai, docker, homelab, machine-learning, meme, self-hosted, semantic-search, vector-database
    COPY-PASTE FIX
    ai, docker, homelab, machine-learning, meme, self-hosted, semantic-search, vector-database, meme-management, image-search-engine
  • mediumabout#3
    Enhance the 'About' description to emphasize its completeness as a solution

    Why:

    CURRENT
    The open source Meme Search Engine and Finder. Free and built to self-host locally with Python, Ruby, and Docker.
    COPY-PASTE FIX
    A complete, open-source Meme Search Engine and Finder. Free and built to self-host locally with Python, Ruby, and Docker, it's designed as a robust solution for personal meme collection management and retrieval.

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 neonwatty/meme-search
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
immich-app/immich
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. immich-app/immich · recommended 1×
  2. photoprism/photoprism · recommended 1×
  3. nextcloud/memories · recommended 1×
  4. Digikam · recommended 1×
  5. openai/CLIP · recommended 1×
  • CATEGORY QUERY
    How to build a self-hosted AI-powered search engine for personal image collections?
    you: not recommended
    AI recommended (in order):
    1. Immich (immich-app/immich)
    2. Photoprism (photoprism/photoprism)
    3. Nextcloud Memories (nextcloud/memories)
    4. Digikam
    5. CLIP (openai/CLIP)
    6. Elasticsearch (elastic/elasticsearch)
    7. OpenSearch (opensearch-project/OpenSearch)
    8. Faiss (facebookresearch/faiss)
    9. PhotoStructure

    AI recommended 9 alternatives but never named neonwatty/meme-search. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools use vector databases for local semantic image search?
    you: not recommended
    AI recommended (in order):
    1. Faiss
    2. Annoy
    3. Hnswlib
    4. Milvus Lite
    5. Weaviate
    6. Qdrant

    AI recommended 6 alternatives but never named neonwatty/meme-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 neonwatty/meme-search?
    pass
    AI named neonwatty/meme-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 neonwatty/meme-search in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name neonwatty/meme-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?

  • In one sentence, what problem does the repo neonwatty/meme-search solve, and who is the primary audience?
    pass
    AI named neonwatty/meme-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

Drop this badge into the README of neonwatty/meme-search. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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neonwatty/meme-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