RRepoGEO

REPOGEO REPORT · LITE

TsinghuaDatabaseGroup/AIDB

Default branch main · commit 68ed2987 · scanned 6/6/2026, 9:17:51 AM

GitHub: 822 stars · 97 forks

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 TsinghuaDatabaseGroup/AIDB, 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:

    CURRENT
    (none)
    COPY-PASTE FIX
    autonomous-database, ai4db, db4ai, llm4db, database-research, database-tuning, query-optimization, machine-learning-databases, survey, tutorial
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., LICENSE.md) in the repository root with the chosen open-source license text.
  • mediumabout#3
    Update the repository's 'About' description

    Why:

    CURRENT
    ai4db and db4ai work
    COPY-PASTE FIX
    A comprehensive collection of research papers and practices in autonomous databases, covering AI for databases (AI4DB) and databases for AI (DB4AI), including LLM4DB, configuration, query optimization, and design.

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 TsinghuaDatabaseGroup/AIDB
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DBTune
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. DBTune · recommended 2×
  2. Everest · recommended 1×
  3. OtterTune · recommended 1×
  4. Google Cloud SQL Insights · recommended 1×
  5. Amazon RDS Performance Insights · recommended 1×
  • CATEGORY QUERY
    What tools can help automate database configuration and performance tuning using AI?
    you: not recommended
    AI recommended (in order):
    1. Everest
    2. OtterTune
    3. DBTune
    4. Google Cloud SQL Insights
    5. Amazon RDS Performance Insights
    6. Microsoft Azure SQL Database Intelligent Performance
    7. Oracle Autonomous Database

    AI recommended 7 alternatives but never named TsinghuaDatabaseGroup/AIDB. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking solutions to optimize database query plans and performance using machine learning techniques.
    you: not recommended
    AI recommended (in order):
    1. Bao
    2. DBTune
    3. Learned Cardinality Estimators
    4. Neo
    5. Google Cloud SQL
    6. AWS RDS
    7. scikit-learn
    8. TensorFlow
    9. PyTorch

    AI recommended 9 alternatives but never named TsinghuaDatabaseGroup/AIDB. 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 TsinghuaDatabaseGroup/AIDB?
    pass
    AI named TsinghuaDatabaseGroup/AIDB explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of TsinghuaDatabaseGroup/AIDB. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
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TsinghuaDatabaseGroup/AIDB — 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