RRepoGEO

REPOGEO REPORT · LITE

InteractiveNLP-Team/RoleLLM-public

Default branch main · commit 131a157c · scanned 6/15/2026, 10:43:04 AM

GitHub: 525 stars · 18 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 InteractiveNLP-Team/RoleLLM-public, 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 core value proposition to the very top of the README

    Why:

    CURRENT
    <h1> 👨‍🎤 RoleLLM 🪅 </h1>
    COPY-PASTE FIX
    <h1> 👨‍🎤 RoleLLM 🪅: A Framework for Benchmarking, Eliciting, and Enhancing LLM Role-Playing Abilities </h1>
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    llm, large-language-models, role-playing, character-ai, llm-benchmarking, instruction-tuning, nlp, persona-generation, context-instruct, rolebench
  • mediumlicense#3
    Add an MIT LICENSE file

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a file named LICENSE in the repository root containing the full text of the MIT License.

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 InteractiveNLP-Team/RoleLLM-public
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Scale AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Scale AI · recommended 2×
  2. Appen · recommended 2×
  3. Character.AI · recommended 1×
  4. PersonaChat · recommended 1×
  5. DailyDialog · recommended 1×
  • CATEGORY QUERY
    How to improve large language models' ability to realistically role-play diverse characters?
    you: not recommended
    AI recommended (in order):
    1. Character.AI
    2. PersonaChat
    3. DailyDialog
    4. Scale AI
    5. Appen

    AI recommended 5 alternatives but never named InteractiveNLP-Team/RoleLLM-public. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools exist for evaluating and benchmarking LLM performance in character simulation?
    you: not recommended
    AI recommended (in order):
    1. Surge AI
    2. Scale AI
    3. Appen
    4. MT-bench
    5. AlpacaEval
    6. HELM
    7. LangChain
    8. Ragas
    9. spaCy
    10. NLTK
    11. Hugging Face Transformers
    12. distilbert-base-uncased-finetuned-sst-2-english
    13. cardiffnlp/twitter-roberta-base-sentiment-latest
    14. Sentence-BERT
    15. textstat
    16. Weights & Biases (W&B) Prompts
    17. MLflow

    AI recommended 17 alternatives but never named InteractiveNLP-Team/RoleLLM-public. 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 InteractiveNLP-Team/RoleLLM-public?
    pass
    AI did not name InteractiveNLP-Team/RoleLLM-public — 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 InteractiveNLP-Team/RoleLLM-public in production, what risks or prerequisites should they evaluate first?
    pass
    AI named InteractiveNLP-Team/RoleLLM-public 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 InteractiveNLP-Team/RoleLLM-public solve, and who is the primary audience?
    pass
    AI did not name InteractiveNLP-Team/RoleLLM-public — 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

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MARKDOWN (README)
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InteractiveNLP-Team/RoleLLM-public — 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