RRepoGEO

REPOGEO REPORT · LITE

spring-ai-alibaba/DataAgent

Default branch main · commit 599c1310 · scanned 5/20/2026, 12:26:37 PM

GitHub: 1,937 stars · 455 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
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 spring-ai-alibaba/DataAgent, 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
    ai-agent, text-to-sql, python-analysis, intelligent-reporting, spring-ai, alibaba-cloud, llm, data-analysis, enterprise-ai, mcp-server, rag-enhancement
  • highreadme#2
    Clarify the repository's role as an AI agent solution in the README subtitle

    Why:

    CURRENT
    <strong>基于 <a href="https://github.com/alibaba/spring-ai-alibaba" target="_blank">Spring AI Alibaba</a> 的企业级智能数据分析师</strong>
    COPY-PASTE FIX
    <strong>基于 <a href="https://github.com/alibaba/spring-ai-alibaba" target="_blank">Spring AI Alibaba</a> 的企业级智能数据分析 Agent 解决方案，赋能 Text-to-SQL 与 Python 深度分析</strong>
  • mediumhomepage#3
    Add the project homepage URL

    Why:

    COPY-PASTE FIX
    https://deepwiki.com/spring-ai-alibaba/DataAgent

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 spring-ai-alibaba/DataAgent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Databricks Lakehouse Platform
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Databricks Lakehouse Platform · recommended 2×
  2. Unity Catalog · recommended 2×
  3. BigQuery · recommended 2×
  4. Dataiku · recommended 1×
  5. OpenAI's GPT-4 · recommended 1×
  • CATEGORY QUERY
    How to automate complex data analysis including Text-to-SQL and Python scripting with AI?
    you: not recommended
    AI recommended (in order):
    1. Dataiku
    2. OpenAI's GPT-4
    3. Google's Gemini
    4. Databricks Lakehouse Platform
    5. Unity Catalog
    6. Databricks SQL
    7. Apache Spark
    8. KNIME Analytics Platform
    9. Microsoft Azure Machine Learning
    10. Azure Data Factory
    11. Azure SQL Database
    12. Azure OpenAI Service
    13. Google Cloud Platform
    14. Vertex AI
    15. BigQuery
    16. Cloud Workflows
    17. Cloud Composer
    18. Apache Airflow

    AI recommended 18 alternatives but never named spring-ai-alibaba/DataAgent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an enterprise solution to generate intelligent data reports using large language models.
    you: not recommended
    AI recommended (in order):
    1. Microsoft Azure OpenAI Service
    2. Azure Machine Learning
    3. Power BI
    4. Google Cloud Vertex AI
    5. BigQuery
    6. Looker
    7. Databricks Lakehouse Platform
    8. MLflow
    9. Unity Catalog
    10. Tableau
    11. Amazon SageMaker
    12. Amazon Bedrock
    13. Amazon QuickSight
    14. Hugging Face Enterprise Hub
    15. Snowflake

    AI recommended 15 alternatives but never named spring-ai-alibaba/DataAgent. 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 spring-ai-alibaba/DataAgent?
    pass
    AI named spring-ai-alibaba/DataAgent explicitly

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

  • If a team adopts spring-ai-alibaba/DataAgent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named spring-ai-alibaba/DataAgent 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 spring-ai-alibaba/DataAgent solve, and who is the primary audience?
    pass
    AI named spring-ai-alibaba/DataAgent 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 spring-ai-alibaba/DataAgent. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/spring-ai-alibaba/DataAgent.svg)](https://repogeo.com/en/r/spring-ai-alibaba/DataAgent)
HTML
<a href="https://repogeo.com/en/r/spring-ai-alibaba/DataAgent"><img src="https://repogeo.com/badge/spring-ai-alibaba/DataAgent.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

spring-ai-alibaba/DataAgent — 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