RRepoGEO

REPOGEO REPORT · LITE

SalesforceAIResearch/xLAM

Default branch main · commit a88aa3ae · scanned 6/7/2026, 12:16:48 AM

GitHub: 623 stars · 55 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 SalesforceAIResearch/xLAM, 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 intro to clarify xLAM's identity and competitive role

    Why:

    CURRENT
    The README starts with navigation links and then 'News,' lacking an immediate, clear definition and competitive positioning.
    COPY-PASTE FIX
    Insert the following paragraph directly after the initial navigation links and before the 'News' section: "**xLAM (Large Action Models)** is a cutting-edge family of models and a comprehensive framework designed to empower AI agent systems by enabling them to perform complex, structured actions. Unlike traditional Large Language Models (LLMs) that primarily focus on text generation, xLAM specializes in action generation and execution, allowing agents to interact with dynamic environments effectively. This makes xLAM a foundational resource for developers building intelligent AI agents, similar to how frameworks like LangChain and LlamaIndex facilitate LLM-based agent development."
  • mediumhomepage#2
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    https://huggingface.co/collections/Salesforce/xlam-models-65f00e2a0a63bbcd1c2dade4
  • lowtopics#3
    Add 'action-models' and 'large-action-models' to repository topics

    Why:

    CURRENT
    actionstudio, agents, agentstudio, llm-agent, llms, xlam
    COPY-PASTE FIX
    actionstudio, agents, agentstudio, llm-agent, llms, xlam, action-models, large-action-models

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 SalesforceAIResearch/xLAM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. Microsoft Semantic Kernel · recommended 2×
  4. OpenAI Assistants API · recommended 2×
  5. Haystack · recommended 1×
  • CATEGORY QUERY
    What are the best frameworks for building intelligent AI agents that can perform complex actions?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGPT
    5. Microsoft Semantic Kernel
    6. OpenAI Assistants API
    7. Rasa

    AI recommended 7 alternatives but never named SalesforceAIResearch/xLAM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I integrate large action models to enhance my LLM-based agent's capabilities?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Microsoft Semantic Kernel
    4. OpenAI Assistants API
    5. Hugging Face Transformers Agents
    6. GPT-4
    7. Claude 3
    8. Gemini
    9. ROS (Robot Operating System)

    AI recommended 9 alternatives but never named SalesforceAIResearch/xLAM. 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 SalesforceAIResearch/xLAM?
    pass
    AI named SalesforceAIResearch/xLAM explicitly

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

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