RRepoGEO

REPOGEO REPORT · LITE

X-PLUG/CValues

Default branch main · commit 3018d388 · scanned 6/11/2026, 5:32:40 AM

GitHub: 556 stars · 22 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 X-PLUG/CValues, 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
    Clarify project domain and purpose in README's opening

    Why:

    CURRENT
    The current README starts with a Chinese title and then a '简介' (Introduction) section.
    COPY-PASTE FIX
    Add the following English statement at the very top of the README, immediately after the main title: 'X-PLUG/CValues is a research project and benchmark for evaluating and aligning the values of Chinese Large Language Models (LLMs), focusing on safety and responsibility. This is NOT a C/C++ library for generic value representation.'
  • hightopics#2
    Add more specific topics for LLM ethics and alignment

    Why:

    CURRENT
    benchmark, chinese-llms, evaluation, human-values, llms, multi-choice, responsibility, safety
    COPY-PASTE FIX
    benchmark, chinese-llms, evaluation, human-values, llms, multi-choice, responsibility, safety, llm-ethics, llm-alignment, responsible-ai, ai-safety
  • mediumhomepage#3
    Add a project homepage URL

    Why:

    COPY-PASTE FIX
    https://modelscope.cn/datasets/damo/CValues-Comparison/summary

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 X-PLUG/CValues
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Evals
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Evals · recommended 2×
  2. Hugging Face Transformers · recommended 1×
  3. Baidu ERNIE-Kit · recommended 1×
  4. Tencent Cloud's NLP Services · recommended 1×
  5. Alibaba Cloud's NLP Services · recommended 1×
  • CATEGORY QUERY
    How to evaluate the safety and human values of large language models specifically for Chinese language?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Evals
    2. Hugging Face Transformers
    3. Baidu ERNIE-Kit
    4. Tencent Cloud's NLP Services
    5. Alibaba Cloud's NLP Services
    6. Label Studio
    7. Prodigy

    AI recommended 7 alternatives but never named X-PLUG/CValues. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools for benchmarking large language model ethical alignment and responsibility using automated methods?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Evaluate Library
    2. Microsoft Responsible AI Toolbox (RAI Toolbox)
    3. IBM AI Fairness 360 (AIF360)
    4. Google's What-If Tool (WIT)
    5. Fiddler AI Observability Platform
    6. Arthur AI Platform
    7. OpenAI Evals

    AI recommended 7 alternatives but never named X-PLUG/CValues. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 X-PLUG/CValues?
    pass
    AI named X-PLUG/CValues explicitly

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

  • If a team adopts X-PLUG/CValues in production, what risks or prerequisites should they evaluate first?
    pass
    AI named X-PLUG/CValues 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 X-PLUG/CValues solve, and who is the primary audience?
    pass
    AI named X-PLUG/CValues 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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X-PLUG/CValues — 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