RRepoGEO

REPOGEO REPORT · LITE

whoiskatrin/sql-translator

Default branch main · commit fb7d30f3 · scanned 5/9/2026, 8:12:52 PM

GitHub: 4,311 stars · 374 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 whoiskatrin/sql-translator, 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 README opening to emphasize AI-powered NL-to-SQL/SQL-to-NL

    Why:

    CURRENT
    Welcome to the SQL and Natural Language Translator! This tool is designed to make it easy for anyone to translate SQL (Structured Query Language) commands into natural language and vice versa. SQL is a programming language used to manage and manipulate data in relational databases, and while it's a powerful tool, it can also be quite complex and difficult to understand. On the other hand, natural language is the language that we speak and write in everyday life, and it's often the preferred way to communicate for people who are not familiar with technical jargon. With the SQL and Natural Language Translator, you don't need to be a SQL expert to understand what's going on in your database, or to write SQL queries. You can simply type in your query in natural language and get the corresponding SQL code, or type in your SQL code and get a human-readable translation.This project is 100% free and open source.
    COPY-PASTE FIX
    SQL Translator is an AI-powered open-source tool that effortlessly converts natural language queries into SQL code and translates complex SQL commands into plain English. Designed for anyone from data analysts to developers, it simplifies database interaction without requiring deep SQL expertise.
  • hightopics#2
    Add specific topics for NL-to-SQL and AI

    Why:

    CURRENT
    data-analysis, data-engineering, dataquery, datascience, dataset, openai, postgresql, query, sql
    COPY-PASTE FIX
    natural-language-to-sql, sql-to-natural-language, llm, generative-ai, data-analysis, data-engineering, dataquery, datascience, dataset, openai, postgresql, query, sql
  • mediumreadme#3
    Add a 'Why SQL Translator?' or 'Comparison' section to README

    Why:

    COPY-PASTE FIX
    ## Why SQL Translator?
Unlike general AI models or SQL dialect translators, SQL Translator is specifically engineered for bidirectional translation between natural language and SQL. It's an open-source, dedicated solution for users who need to quickly generate SQL from plain English or understand complex queries without deep SQL knowledge, focusing purely on the NL-to-SQL and SQL-to-NL use cases.

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 whoiskatrin/sql-translator
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SQLFlow
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. SQLFlow · recommended 2×
  2. OpenAI GPT-4 / GPT-3.5 · recommended 1×
  3. Google Gemini · recommended 1×
  4. Hugging Face Transformers · recommended 1×
  5. Dataherald · recommended 1×
  • CATEGORY QUERY
    How can I generate SQL queries from natural language descriptions using an AI tool?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4 / GPT-3.5
    2. Google Gemini
    3. Hugging Face Transformers
    4. SQLFlow
    5. Dataherald
    6. Vanna.ai

    AI recommended 6 alternatives but never named whoiskatrin/sql-translator. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools help translate complex SQL queries into plain English explanations?
    you: not recommended
    AI recommended (in order):
    1. SQLFlow
    2. Hugging Face Transformers Library
    3. OpenNMT
    4. sqlparse
    5. JSQLParser
    6. Amundsen
    7. DataHub
    8. sqlfluff

    AI recommended 8 alternatives but never named whoiskatrin/sql-translator. 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 whoiskatrin/sql-translator?
    pass
    AI did not name whoiskatrin/sql-translator — 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?

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

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

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whoiskatrin/sql-translator — 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