RRepoGEO

REPOGEO REPORT · LITE

OpenGenerativeAI/llm-colosseum

Default branch main · commit f51f0b04 · scanned 6/22/2026, 5:01:52 PM

GitHub: 1,483 stars · 180 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 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 the README's opening statement to clarify its core purpose

    Why:

    CURRENT
    # Evaluate LLMs in real time with Street Fighter III
    COPY-PASTE FIX
    # llm-colosseum: An Innovative Platform for Real-time LLM Evaluation and Benchmarking
  • mediumreadme#2
    Add a clear problem statement/value proposition early in the README

    Why:

    COPY-PASTE FIX
    Tired of static LLM benchmarks? llm-colosseum offers a dynamic, real-time environment to evaluate LLMs' decision-making, adaptability, and strategic thinking in complex, interactive scenarios, going beyond traditional datasets.
  • lowtopics#3
    Expand repository topics with more specific LLM evaluation terms

    Why:

    CURRENT
    benchmark, genai, llm, streetfighterai
    COPY-PASTE FIX
    benchmark, genai, llm, streetfighterai, llm-evaluation, llm-benchmarking, ai-evaluation, real-time-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 OpenGenerativeAI/llm-colosseum
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Optimizely
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Optimizely · recommended 2×
  2. LaunchDarkly · recommended 2×
  3. prometheus/prometheus · recommended 1×
  4. grafana/grafana · recommended 1×
  5. OpenTelemetry · recommended 1×
  • CATEGORY QUERY
    How can I assess large language model performance in real-time decision-making scenarios?
    you: not recommended
    AI recommended (in order):
    1. Prometheus (prometheus/prometheus)
    2. Grafana (grafana/grafana)
    3. OpenTelemetry
    4. Locust (locustio/locust)
    5. JMeter
    6. Scale AI
    7. Appen
    8. Surge AI
    9. OpenAI Evals (openai/evals)
    10. LangChain Evaluation Module (langchain-ai/langchain)
    11. Optimizely
    12. LaunchDarkly
    13. Garak (leondf/garak)
    14. OpenAI Moderation API
    15. Google Cloud Content Moderation
    16. LIME (marcotcr/lime)
    17. SHAP (shap/shap)

    AI recommended 17 alternatives but never named OpenGenerativeAI/llm-colosseum. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking innovative methods for benchmarking LLMs beyond traditional static datasets and metrics.
    you: not recommended
    AI recommended (in order):
    1. HELM (Holistic Evaluation of Language Models)
    2. Dynabench
    3. Adversarial NLI (ANLI)
    4. Gauntlet (from Google)
    5. TruthfulQA
    6. Optimizely
    7. LaunchDarkly

    AI recommended 7 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 named OpenGenerativeAI/llm-colosseum explicitly

    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 named OpenGenerativeAI/llm-colosseum explicitly

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

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MARKDOWN (README)
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OpenGenerativeAI/llm-colosseum — 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