RRepoGEO

REPOGEO REPORT · LITE

kelindar/search

Default branch main · commit b4c4ef13 · scanned 6/2/2026, 6:37:44 PM

GitHub: 550 stars · 24 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 kelindar/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 H1 and opening paragraph to emphasize 'embedded Go library for GGUF'

    Why:

    CURRENT
    # Semantic Search

This library was created to provide an **easy and efficient solution for embedding and vector search**
    COPY-PASTE FIX
    # kelindar/search: Embedded Go Vector Search for GGUF Models

kelindar/search is an **embedded Go library** for **efficient vector search and semantic embeddings**, specifically designed for **small to medium-scale projects** using **GGUF BERT models** and **llama.cpp without cgo**.
  • mediumtopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    ai, bert, embeddings, gguf, gpu, llamacpp, search-engine, semantic-search, simd, vector-search
    COPY-PASTE FIX
    ai, bert, embeddings, gguf, gpu, llamacpp, search-engine, semantic-search, simd, vector-search, go-library, embedded, purego
  • mediumhomepage#3
    Add a project homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://[YOUR_PROJECT_HOMEPAGE_URL_HERE]

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 kelindar/search
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
gonum/gonum
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. gonum/gonum · recommended 2×
  2. facebookresearch/faiss · recommended 1×
  3. nmslib/hnswlib · recommended 1×
  4. Pinecone · recommended 1×
  5. weaviate/weaviate · recommended 1×
  • CATEGORY QUERY
    How to implement efficient semantic search with vector embeddings in Go for smaller datasets?
    you: not recommended
    AI recommended (in order):
    1. Faiss (facebookresearch/faiss)
    2. Hnswlib (nmslib/hnswlib)
    3. Pinecone
    4. Weaviate (weaviate/weaviate)
    5. Qdrant (qdrant/qdrant)
    6. Milvus (milvus-io/milvus)
    7. gonum/matrix (gonum/gonum)
    8. gonum/floats (gonum/gonum)

    AI recommended 8 alternatives but never named kelindar/search. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an embedded Go library for vector search using GGUF models with GPU acceleration.
    you: not recommended
    AI recommended (in order):
    1. llama.cpp
    2. TensorFlow Lite
    3. ONNX Runtime
    4. hnswlib
    5. FAISS

    AI recommended 5 alternatives but never named kelindar/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 kelindar/search?
    pass
    AI named kelindar/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 kelindar/search in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kelindar/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 kelindar/search solve, and who is the primary audience?
    pass
    AI named kelindar/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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kelindar/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