RRepoGEO

REPOGEO REPORT · LITE

AMA-CMFAI/LAMBDA

Default branch main · commit d124b5e1 · scanned 6/13/2026, 5:21:49 AM

GitHub: 579 stars · 54 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 AMA-CMFAI/LAMBDA, 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
    Elevate core project definition in README

    Why:

    CURRENT
    The current README excerpt shows the core definition under "Github Version" after web app launch details.
    COPY-PASTE FIX
    Move the sentence "We introduce **LAMBDA**, a novel open-source, code-free multi-agent data analysis system that harnesses the power of large models." to be the very first paragraph after the main title/badges, before any web app launch details.
  • mediumtopics#2
    Add specific data analysis and no-code topics

    Why:

    CURRENT
    agents, ai, generative-ai, large-language-models
    COPY-PASTE FIX
    agents, ai, generative-ai, large-language-models, data-analysis, no-code
  • lowhomepage#3
    Update repository homepage to primary project site

    Why:

    CURRENT
    https://arxiv.org/abs/2407.17535
    COPY-PASTE FIX
    https://lambda.com.ai

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 AMA-CMFAI/LAMBDA
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ChatGPT Plus / Enterprise with Advanced Data Analysis
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ChatGPT Plus / Enterprise with Advanced Data Analysis · recommended 1×
  2. Microsoft Copilot for Microsoft 365 · recommended 1×
  3. Google Gemini Advanced · recommended 1×
  4. Tableau Pulse · recommended 1×
  5. DataRobot · recommended 1×
  • CATEGORY QUERY
    How can I perform complex data analysis without writing code, using AI agents?
    you: not recommended
    AI recommended (in order):
    1. ChatGPT Plus / Enterprise with Advanced Data Analysis
    2. Microsoft Copilot for Microsoft 365
    3. Google Gemini Advanced
    4. Tableau Pulse
    5. DataRobot
    6. H2O Driverless AI

    AI recommended 6 alternatives but never named AMA-CMFAI/LAMBDA. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best large model systems for iterative and generative data analysis?
    you: not recommended
    AI recommended (in order):
    1. Databricks Lakehouse Platform
    2. Google Cloud Vertex AI Workbench
    3. Amazon SageMaker Studio
    4. Hugging Face Ecosystem
    5. Weights & Biases (W&B) (wandb/wandb)
    6. Domino Data Lab
    7. Anaconda Enterprise

    AI recommended 7 alternatives but never named AMA-CMFAI/LAMBDA. 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 AMA-CMFAI/LAMBDA?
    pass
    AI named AMA-CMFAI/LAMBDA explicitly

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

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

    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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MARKDOWN (README)
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AMA-CMFAI/LAMBDA — 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