RRepoGEO

REPOGEO REPORT · LITE

OpenGenerativeAI/llm-colosseum

Default branch main · commit f51f0b04 · scanned 5/12/2026, 10:51:50 AM

GitHub: 1,481 stars · 181 forks

AI VISIBILITY SCORE
27 /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
1 / 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 OpenGenerativeAI/llm-colosseum, 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 opening to clarify LLM evaluation focus

    Why:

    CURRENT
    Make LLM fight each other in real time in Street Fighter III.
    
    Which LLM will be the best fighter ?
    COPY-PASTE FIX
    This project introduces a novel, real-time benchmark for Large Language Models (LLMs) by pitting them against each other in Street Fighter III. It's designed to evaluate LLM performance in strategic thinking, real-time decision-making, and adaptability within a dynamic game environment.
  • mediumtopics#2
    Add more specific topics for LLM evaluation and strategic AI

    Why:

    CURRENT
    benchmark, genai, llm, streetfighterai
    COPY-PASTE FIX
    benchmark, genai, llm, streetfighterai, llm-evaluation, ai-agents, strategic-ai, real-time-decision-making
  • mediumabout#3
    Enhance repository description to highlight unique evaluation methodology

    Why:

    CURRENT
    Benchmark LLMs by fighting in Street Fighter 3! The new way to evaluate the quality of an LLM
    COPY-PASTE FIX
    A novel benchmark for LLMs: evaluate their strategic thinking and real-time decision-making by having them fight in Street Fighter 3. Discover a new way to assess LLM quality beyond traditional metrics.

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 OpenGenerativeAI/llm-colosseum
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Farama-Foundation/Gymnasium
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Farama-Foundation/Gymnasium · recommended 1×
  2. Unity-Technologies/ml-agents · recommended 1×
  3. minerllabs/minerl · recommended 1×
  4. Microsoft/malmo · recommended 1×
  5. microsoft/textworld · recommended 1×
  • CATEGORY QUERY
    How to evaluate LLM performance using interactive, real-time game environments?
    you: not recommended
    AI recommended (in order):
    1. Farama Foundation Gymnasium (Farama-Foundation/Gymnasium)
    2. Unity ML-Agents Toolkit (Unity-Technologies/ml-agents)
    3. MineRL (minerllabs/minerl)
    4. Project Malmo (Microsoft/malmo)
    5. TextWorld (microsoft/textworld)
    6. Jericho (mike-gifford/jericho)
    7. Phaser.js (photonstorm/phaser)
    8. Three.js (mrdoob/three.js)
    9. Flask (pallets/flask)
    10. FastAPI (tiangolo/fastapi)

    AI recommended 10 alternatives but never named OpenGenerativeAI/llm-colosseum. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help benchmark large language models for strategic thinking and real-time decision-making?
    you: not recommended
    AI recommended (in order):
    1. HELM
    2. BIG-bench
    3. AgentBench
    4. OpenAI Evals
    5. LangChain
    6. RAGAS
    7. Scale AI
    8. Appen

    AI recommended 8 alternatives but never named OpenGenerativeAI/llm-colosseum. 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 OpenGenerativeAI/llm-colosseum?
    pass
    AI did not name OpenGenerativeAI/llm-colosseum — 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?

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