RRepoGEO

REPOGEO REPORT · LITE

naver/sqlova

Default branch master · commit fc68af60 · scanned 6/10/2026, 3:17:18 PM

GitHub: 648 stars · 167 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)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 naver/sqlova, 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
  • highabout#1
    Add a concise 'About' description

    Why:

    COPY-PASTE FIX
    A state-of-the-art neural semantic parser that translates natural language utterances into SQL queries, evaluated on the WikiSQL dataset.
  • mediumreadme#2
    Enhance the README's initial positioning

    Why:

    CURRENT
    # SQLova
- SQLova is a neural semantic parser translating natural language utterance to SQL query. The name is originated from the name of our department:  **S**earch & **QLova** (Search & Clova).

### Authors
    COPY-PASTE FIX
    # SQLova: State-of-the-Art Neural Text-to-SQL Parser

SQLova is a powerful neural semantic parser designed to translate natural language utterances directly into SQL queries. This repository provides the code and models for our state-of-the-art solution, achieving high accuracy on the WikiSQL dataset. It's ideal for researchers and developers building robust natural language interfaces for databases.

### Authors

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 naver/sqlova
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 2×
  2. SQLFlow · recommended 2×
  3. OpenAI's GPT-3.5/GPT-4 · recommended 1×
  4. Claude · recommended 1×
  5. Llama 2 · recommended 1×
  • CATEGORY QUERY
    How can I automatically generate SQL queries from natural language descriptions?
    you: not recommended
    AI recommended (in order):
    1. OpenAI's GPT-3.5/GPT-4
    2. Claude
    3. Llama 2
    4. Hugging Face Transformers
    5. SQLFlow
    6. Dataherald
    7. Seek AI

    AI recommended 7 alternatives but never named naver/sqlova. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools exist for building a natural language to database query interface?
    you: not recommended
    AI recommended (in order):
    1. SQLFlow
    2. Spider
    3. Hugging Face Transformers
    4. spaCy
    5. NLTK
    6. AllenNLP
    7. SQLAlchemy

    AI recommended 7 alternatives but never named naver/sqlova. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 naver/sqlova?
    pass
    AI named naver/sqlova explicitly

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

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

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

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naver/sqlova — 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