RRepoGEO

REPOGEO REPORT · LITE

agno-agi/dash

Default branch main · commit dfcf2bed · scanned 5/25/2026, 10:57:23 PM

GitHub: 2,074 stars · 234 forks

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 agno-agi/dash, 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 improve categorization

    Why:

    COPY-PASTE FIX
    ai-agent, data-agent, self-learning, business-intelligence, data-analysis, generative-ai, llm-agent, systems-engineering, conversational-ai
  • highreadme#2
    Add a value proposition sentence to the README's opening

    Why:

    CURRENT
    A **self-learning data agent** built with systems engineering principles. It grounds answers in 6 layers of context and improves with every query.
    COPY-PASTE FIX
    Dash is a **self-learning data agent** built with systems engineering principles, empowering business users and data analysts to get real-time, contextual insights from their data. It grounds answers in 6 layers of context and improves with every query.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://os.agno.com

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 agno-agi/dash
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TensorFlow
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. TensorFlow · recommended 1×
  2. PyTorch · recommended 1×
  3. scikit-learn · recommended 1×
  4. Ray · recommended 1×
  5. Apache Spark · recommended 1×
  • CATEGORY QUERY
    How to build a self-learning AI agent for data analysis and business intelligence?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow
    2. PyTorch
    3. scikit-learn
    4. Ray
    5. Apache Spark
    6. OpenAI Gym
    7. Hugging Face Transformers

    AI recommended 7 alternatives but never named agno-agi/dash. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool for AI-driven data insights that learns from queries and provides contextual answers?
    you: not recommended
    AI recommended (in order):
    1. ThoughtSpot
    2. Tableau CRM
    3. Qlik Sense
    4. Microsoft Power BI
    5. Sisense
    6. Yellowfin BI

    AI recommended 6 alternatives but never named agno-agi/dash. 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 agno-agi/dash?
    pass
    AI named agno-agi/dash explicitly

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

  • If a team adopts agno-agi/dash in production, what risks or prerequisites should they evaluate first?
    pass
    AI named agno-agi/dash 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 agno-agi/dash solve, and who is the primary audience?
    pass
    AI named agno-agi/dash 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 agno-agi/dash. 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/agno-agi/dash.svg)](https://repogeo.com/en/r/agno-agi/dash)
HTML
<a href="https://repogeo.com/en/r/agno-agi/dash"><img src="https://repogeo.com/badge/agno-agi/dash.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

agno-agi/dash — 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