RRepoGEO

REPOGEO REPORT · LITE

Stevenic/vectra

Default branch main · commit dec2dadc · scanned 5/31/2026, 10:26:29 PM

GitHub: 618 stars · 49 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 Stevenic/vectra, 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
  • highreadme#1
    Clarify Node.js focus in README's opening

    Why:

    CURRENT
    # Vectra: a local vector database
...
Vectra is a local, file-backed, in-memory vector database with an optional gRPC server for cross-language access.
    COPY-PASTE FIX
    # Vectra: a local vector database for Node.js
...
Vectra is a local, file-backed, in-memory vector database for Node.js and JavaScript applications, with an optional gRPC server for cross-language access.
  • mediumhomepage#2
    Add a homepage URL to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://github.com/Stevenic/vectra

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 Stevenic/vectra
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LanceDB
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LanceDB · recommended 2×
  2. Milvus Lite · recommended 2×
  3. ChromaDB · recommended 1×
  4. HNSWLib · recommended 1×
  5. Faiss · recommended 1×
  • CATEGORY QUERY
    How to integrate a local vector store for semantic search within a Node.js project?
    you: not recommended
    AI recommended (in order):
    1. ChromaDB
    2. LanceDB
    3. HNSWLib
    4. Faiss
    5. Milvus Lite

    AI recommended 5 alternatives but never named Stevenic/vectra. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an embedded, file-backed vector database alternative to cloud services for offline use.
    you: not recommended
    AI recommended (in order):
    1. Chroma
    2. LanceDB
    3. FAISS
    4. Hnswlib
    5. Milvus Lite

    AI recommended 5 alternatives but never named Stevenic/vectra. 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 Stevenic/vectra?
    pass
    AI named Stevenic/vectra explicitly

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

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

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

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Stevenic/vectra — 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