RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/cwm

Default branch main · commit 7930e029 · scanned 5/30/2026, 11:32:52 PM

GitHub: 874 stars · 71 forks

AI VISIBILITY SCORE
28 /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
2 / 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 facebookresearch/cwm, 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 the README H1 and opening paragraph to specify 'Code Generation LLM'

    Why:

    CURRENT
    # Code World Model

Code World Model (CWM) is a 32-billion-parameter open-weights LLM, to advance research on code generation with world models.
    COPY-PASTE FIX
    # Code World Model (CWM): A 32B-Parameter LLM for Code Generation and Reasoning

This repository contains research artifacts for the Code World Model (CWM), a 32-billion-parameter open-weights Large Language Model specifically designed to advance research on code generation, understanding program state, and multi-turn software engineering tasks.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    large-language-model, llm, code-generation, code-llm, program-synthesis, software-engineering, world-model, research, python
  • mediumlicense#3
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    ## License

This project is licensed under the terms found in the [LICENSE](LICENSE) file. Please review the LICENSE file for specific details regarding usage and distribution.

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 facebookresearch/cwm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Code Llama
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Code Llama · recommended 1×
  2. DeepSeek Coder · recommended 1×
  3. StarCoder2 · recommended 1×
  4. Phind-CodeLlama · recommended 1×
  5. WizardCoder · recommended 1×
  • CATEGORY QUERY
    What open-source large language models are best for code generation and understanding program state?
    you: not recommended
    AI recommended (in order):
    1. Code Llama
    2. DeepSeek Coder
    3. StarCoder2
    4. Phind-CodeLlama
    5. WizardCoder
    6. Mistral-7B-Instruct-v0.2

    AI recommended 6 alternatives but never named facebookresearch/cwm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an LLM to assist with multi-turn software engineering tasks and verifiable code completion.
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. Google Cloud Vertex AI Code Assist
    3. OpenAI GPT-4
    4. Anthropic Claude 3 Opus
    5. Code Llama (facebookresearch/codellama)
    6. Tabnine Enterprise
    7. JetBrains AI Assistant

    AI recommended 7 alternatives but never named facebookresearch/cwm. 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 facebookresearch/cwm?
    pass
    AI named facebookresearch/cwm explicitly

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

  • If a team adopts facebookresearch/cwm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named facebookresearch/cwm 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 facebookresearch/cwm solve, and who is the primary audience?
    pass
    AI did not name facebookresearch/cwm — 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?

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facebookresearch/cwm — 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