RRepoGEO

REPOGEO REPORT · LITE

disler/multi-agent-postgres-data-analytics

Default branch main · commit b1bfdbb4 · scanned 6/8/2026, 9:23:00 AM

GitHub: 878 stars · 183 forks

AI VISIBILITY SCORE
22 /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
1 / 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 disler/multi-agent-postgres-data-analytics, 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
    multi-agent-systems, postgresql, data-analytics, llm, gpt-4, learning-tool, experiment, natural-language-processing
  • highabout#2
    Update the 'About' description for clarity

    Why:

    CURRENT
    The way we interact with our data is changing.
    COPY-PASTE FIX
    An experimental multi-agent system and learning tool for natural language data analytics on PostgreSQL, demonstrating concepts for building autonomous agentic software.
  • mediumhomepage#3
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    [Link to the video series or project landing page]

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 disler/multi-agent-postgres-data-analytics
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. Haystack · recommended 1×
  4. SQLAlchemy · recommended 1×
  5. pandas · recommended 1×
  • CATEGORY QUERY
    How to build autonomous agent systems for analyzing data in a relational database?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. SQLAlchemy
    5. pandas
    6. MindsDB
    7. Auto-GPT
    8. BabyAGI

    AI recommended 8 alternatives but never named disler/multi-agent-postgres-data-analytics. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good experimental projects for learning multi-agent system design with database integration?
    you: not recommended
    AI recommended (in order):
    1. Mesa (mesa-foundation/mesa)
    2. SPADE (jacob-h/spade)
    3. JADE (jade-project/jade)
    4. PostgreSQL
    5. SQLite
    6. MongoDB (mongodb/mongo)
    7. NetLogo (ccl/netlogo)
    8. GAMA (gama-platform/gama)
    9. PostGIS (postgis/postgis)
    10. Neo4j (neo4j/neo4j)
    11. InfluxDB (influxdata/influxdb)
    12. Apache Cassandra (apache/cassandra)
    13. Akka (akka/akka)
    14. Redis (redis/redis)
    15. ROS (Robot Operating System) (ros/ros)

    AI recommended 15 alternatives but never named disler/multi-agent-postgres-data-analytics. 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 disler/multi-agent-postgres-data-analytics?
    pass
    AI did not name disler/multi-agent-postgres-data-analytics — 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 disler/multi-agent-postgres-data-analytics in production, what risks or prerequisites should they evaluate first?
    pass
    AI named disler/multi-agent-postgres-data-analytics 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 disler/multi-agent-postgres-data-analytics solve, and who is the primary audience?
    pass
    AI did not name disler/multi-agent-postgres-data-analytics — 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?

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
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