RRepoGEO

REPOGEO REPORT · LITE

openai/codex-universal

Default branch main · commit 47f4f0eb · scanned 6/1/2026, 11:33:03 PM

GitHub: 945 stars · 250 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 openai/codex-universal, 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 to clarify its purpose as a Docker image for AI code generation environments

    Why:

    CURRENT
    # codex-universal

`codex-universal` is a reference implementation of the base Docker image available in OpenAI Codex.
    COPY-PASTE FIX
    # openai/codex-universal: Base Docker Image for AI Code Generation Environments

This repository provides `openai/codex-universal`, a base Docker image designed to help developers replicate and customize the multi-language programming environments used in OpenAI Codex locally for debugging and development. This is not an identical environment but should help for debugging and development.
  • hightopics#2
    Add relevant topics to improve categorization and recall

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    docker, docker-image, development-environment, multi-language, ai-code-generation, openai-codex, replicate-environment, debugging
  • mediumlicense#3
    Add a LICENSE file to clarify usage rights

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file (e.g., MIT or Apache-2.0) to the repository root, specifying the intended open-source license for `openai/codex-universal`.

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 openai/codex-universal
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 2×
  2. ollama/ollama · recommended 1×
  3. LM Studio · recommended 1×
  4. huggingface/accelerate · recommended 1×
  5. vllm-project/vllm · recommended 1×
  • CATEGORY QUERY
    How to replicate an AI code generation environment locally for debugging and development?
    you: not recommended
    AI recommended (in order):
    1. Ollama (ollama/ollama)
    2. LM Studio
    3. Hugging Face Transformers Library (huggingface/transformers)
    4. transformers (huggingface/transformers)
    5. accelerate (huggingface/accelerate)
    6. vLLM (vllm-project/vllm)
    7. LocalAI (mudler/LocalAI)
    8. llama.cpp (ggerganov/llama.cpp)
    9. llama-cpp-python (abetlen/llama-cpp-python)

    AI recommended 9 alternatives but never named openai/codex-universal. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good base Docker images for multi-language development environments, including Python and Java?
    you: not recommended
    AI recommended (in order):
    1. Eclipse Temurin (adoptium/temurin-build)
    2. Ubuntu
    3. Debian
    4. Alpine Linux
    5. Official Python images (docker-library/python)
    6. Official OpenJDK images (docker-library/openjdk)

    AI recommended 6 alternatives but never named openai/codex-universal. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 openai/codex-universal?
    pass
    AI named openai/codex-universal explicitly

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

  • If a team adopts openai/codex-universal in production, what risks or prerequisites should they evaluate first?
    pass
    AI named openai/codex-universal 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 openai/codex-universal solve, and who is the primary audience?
    pass
    AI named openai/codex-universal 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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite