RRepoGEO

REPOGEO REPORT · LITE

cfahlgren1/natural-sql

Default branch main · commit 5c452c1c · scanned 6/14/2026, 8:17:18 PM

GitHub: 864 stars · 22 forks

AI VISIBILITY SCORE
28 /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
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 cfahlgren1/natural-sql, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    text-to-sql, natural-language-to-sql, nl2sql, llm, large-language-models, sql-generation, database-tools, generative-ai
  • highreadme#2
    Clarify the unique approach in the README's opening paragraph

    Why:

    CURRENT
    NaturalSQL by ChatDB is a series of models with state-of-the-art performance on Text to SQL instructions.
    COPY-PASTE FIX
    NaturalSQL by ChatDB is a series of state-of-the-art Text-to-SQL LLMs, uniquely leveraging OpenAI's function calling API for reliable and structured SQL generation from natural language instructions.
  • mediumabout#3
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    [Link to a relevant project page, demo, or documentation if available, or the HuggingFace model page mentioned in the README]

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 cfahlgren1/natural-sql
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SQLFlow
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. SQLFlow · recommended 1×
  2. PyTorch · recommended 1×
  3. TensorFlow · recommended 1×
  4. Hugging Face Transformers · recommended 1×
  5. T5 · recommended 1×
  • CATEGORY QUERY
    How can I convert natural language questions into accurate SQL queries?
    you: not recommended
    AI recommended (in order):
    1. SQLFlow
    2. PyTorch
    3. TensorFlow
    4. Hugging Face Transformers
    5. T5
    6. BART
    7. GPT-2/GPT-3
    8. Microsoft LUIS
    9. Google Dialogflow
    10. Rasa
    11. Apache Calcite

    AI recommended 11 alternatives but never named cfahlgren1/natural-sql. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best performing models for generating SQL from natural language?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. GPT-3.5 Turbo
    3. Code Llama
    4. StarCoder
    5. StarCoder2
    6. SQLCoder
    7. Gemini

    AI recommended 7 alternatives but never named cfahlgren1/natural-sql. 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 cfahlgren1/natural-sql?
    pass
    AI did not name cfahlgren1/natural-sql — 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 cfahlgren1/natural-sql in production, what risks or prerequisites should they evaluate first?
    pass
    AI named cfahlgren1/natural-sql 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 cfahlgren1/natural-sql solve, and who is the primary audience?
    pass
    AI named cfahlgren1/natural-sql explicitly

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

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  • Brand-free category queries5 vs 2 in Lite
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