RRepoGEO

REPOGEO REPORT · LITE

CSHaitao/Awesome-LLMs-as-Judges

Default branch main · commit d89ed424 · scanned 6/16/2026, 6:13:10 PM

GitHub: 590 stars · 35 forks

AI VISIBILITY SCORE
17 /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
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 CSHaitao/Awesome-LLMs-as-Judges, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm-as-a-judge, llm-evaluation, large-language-models, survey, awesome-list, nlp, generative-ai, ai-judges, evaluation-methods, research-papers
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root directory with an appropriate open-source license (e.g., MIT, Apache-2.0, GPL-3.0) to clarify usage terms.
  • mediumhomepage#3
    Set the repository's homepage URL

    Why:

    COPY-PASTE FIX
    Set the repository's homepage URL to the official paper link or a dedicated project page for the survey.

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 CSHaitao/Awesome-LLMs-as-Judges
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI API
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI API · recommended 2×
  2. LangChain · recommended 2×
  3. LlamaIndex · recommended 2×
  4. Ragas · recommended 2×
  5. GPT-4 · recommended 1×
  • CATEGORY QUERY
    What are effective methods for evaluating large language model outputs using AI judges?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. OpenAI API
    3. FastChat `arena`
    4. LangChain
    5. LlamaIndex
    6. Ragas
    7. DeepEval
    8. NVIDIA NeMo Guardrails
    9. Microsoft's Guidance
    10. Anthropic Claude
    11. Humanloop
    12. Sentence-BERT (SBERT)
    13. OpenAI Embeddings API
    14. Hugging Face Transformers library

    AI recommended 14 alternatives but never named CSHaitao/Awesome-LLMs-as-Judges. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking resources on leveraging large language models for automated content evaluation and quality assessment.
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Anthropic API
    3. Google Cloud Vertex AI
    4. Hugging Face Transformers Library
    5. LangChain
    6. LlamaIndex
    7. W&B Prompts
    8. Ragas

    AI recommended 8 alternatives but never named CSHaitao/Awesome-LLMs-as-Judges. 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 CSHaitao/Awesome-LLMs-as-Judges?
    pass
    AI did not name CSHaitao/Awesome-LLMs-as-Judges — 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 CSHaitao/Awesome-LLMs-as-Judges in production, what risks or prerequisites should they evaluate first?
    pass
    AI named CSHaitao/Awesome-LLMs-as-Judges 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 CSHaitao/Awesome-LLMs-as-Judges solve, and who is the primary audience?
    pass
    AI did not name CSHaitao/Awesome-LLMs-as-Judges — 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?

Embed your GEO score

Drop this badge into the README of CSHaitao/Awesome-LLMs-as-Judges. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/CSHaitao/Awesome-LLMs-as-Judges.svg)](https://repogeo.com/en/r/CSHaitao/Awesome-LLMs-as-Judges)
HTML
<a href="https://repogeo.com/en/r/CSHaitao/Awesome-LLMs-as-Judges"><img src="https://repogeo.com/badge/CSHaitao/Awesome-LLMs-as-Judges.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

CSHaitao/Awesome-LLMs-as-Judges — 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