RRepoGEO

REPOGEO REPORT · LITE

bruin-data/dac

Default branch main · commit 0da1a3c9 · scanned 6/9/2026, 2:52:30 AM

GitHub: 695 stars · 32 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 bruin-data/dac, 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
  • highreadme#1
    Reposition README H1 and intro to disambiguate 'DAC' and emphasize 'Dashboard-as-Code'

    Why:

    CURRENT
    # DAC

DAC is a Dashboard-as-Code tool for defining, validating, and serving dashboards from YAML and TSX.
    COPY-PASTE FIX
    # DAC: Dashboard-as-Code for AI Agents

DAC (Dashboard-as-Code) is a powerful tool for defining, validating, and serving interactive dashboards from YAML and TSX. It is *not* a Data Access Control system or a generic 'Data as Code' framework for data assets, but rather a specialized platform for building reviewable dashboards with a built-in semantic layer and AI agent capabilities.
  • mediumtopics#2
    Expand repository topics to include common dashboarding and BI keywords

    Why:

    CURRENT
    ai-agents, business-intelligence, dashboard, semantic-layer
    COPY-PASTE FIX
    ai-agents, business-intelligence, dashboard, semantic-layer, data-visualization, analytics, declarative-ui, yaml, jsx, web-app
  • lowreadme#3
    Add a 'Comparison with Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, e.g., `## Comparison with Alternatives` or `## Why DAC?` that outlines how DAC differs from tools like Streamlit, Plotly Dash, Grafana, and Looker, especially highlighting its Dashboard-as-Code, AI agent, and built-in semantic layer aspects.

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 bruin-data/dac
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Streamlit
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Streamlit · recommended 1×
  2. Plotly Dash · recommended 1×
  3. Retool · recommended 1×
  4. Grafana · recommended 1×
  5. Apache Superset · recommended 1×
  • CATEGORY QUERY
    How to define interactive dashboards using declarative configuration like YAML or JSX?
    you: not recommended
    AI recommended (in order):
    1. Streamlit
    2. Plotly Dash
    3. Retool
    4. Grafana
    5. Apache Superset
    6. Perspective

    AI recommended 6 alternatives but never named bruin-data/dac. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool for AI agents to build reviewable dashboards with a built-in semantic layer?
    you: not recommended
    AI recommended (in order):
    1. Looker Studio
    2. Looker
    3. Tableau
    4. Tableau Prep Builder
    5. Tableau Catalog
    6. Power BI
    7. Power BI Dataflows
    8. Azure Purview
    9. Metabase (metabase/metabase)
    10. dbt (dbt-labs/dbt-core)
    11. Superset (apache/superset)
    12. Cube.js (cube-js/cube)

    AI recommended 12 alternatives but never named bruin-data/dac. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 bruin-data/dac?
    pass
    AI named bruin-data/dac explicitly

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

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

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

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bruin-data/dac — 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