RRepoGEO

REPOGEO REPORT · LITE

chatopera/efaqa-corpus-zh

Default branch master · commit eade3282 · scanned 5/31/2026, 8:17:46 PM

GitHub: 755 stars · 88 forks

AI VISIBILITY SCORE
33 /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
2 / 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 chatopera/efaqa-corpus-zh, 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 top of the README

    Why:

    CURRENT
    The detailed description of the dataset's unique value (largest, multi-turn, mental health specific) appears several paragraphs into the README, after a table and a note.
    COPY-PASTE FIX
    # 心理咨询相关语料库
chatopera/efaqa-corpus-zh 是迄今公开的最大的中文心理咨询对话语料库，专为心理咨询和情感支持领域的AI应用设计。它包含人工标注的多轮对话数据，是训练和微调大型语言模型（LLMs）以构建心理健康聊天机器人的理想选择。
  • mediumtopics#2
    Add more specific topics to improve category visibility

    Why:

    CURRENT
    corpus, natural-language-processing, natural-language-understanding, psychology
    COPY-PASTE FIX
    corpus, natural-language-processing, natural-language-understanding, psychology, mental-health-chatbot, emotional-support-ai, dialogue-corpus, chinese-nlp, llm-training-data
  • mediumreadme#3
    Clarify the licensing model for code and data in the README

    Why:

    CURRENT
    The README states '心理咨询问答语料库的源代码是基于开源许可证分发，但是安装使用过程中，下载的语料文件，需要从证书商店购买证书，才能下载和使用'.
    COPY-PASTE FIX
    ## 许可与使用
本项目源代码遵循开源许可协议分发。然而，下载和使用语料库文件需要从证书商店购买相应的证书。请参阅 https://www.cskefu.com/licenses/v1.html 获取详细信息。

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 chatopera/efaqa-corpus-zh
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
CLUE (Chinese Language Understanding Evaluation) Benchmark
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. CLUE (Chinese Language Understanding Evaluation) Benchmark · recommended 1×
  2. LCCC (Large-scale Chinese Conversational Corpus) · recommended 1×
  3. CODI (Chinese Open-domain Dialogue Dataset) · recommended 1×
  4. Weibo Sentiment Analysis Datasets · recommended 1×
  5. Chinese Medical Question Answering (QA) Datasets · recommended 1×
  • CATEGORY QUERY
    Where can I find a large Chinese dataset for training a mental health chatbot?
    you: not recommended
    AI recommended (in order):
    1. CLUE (Chinese Language Understanding Evaluation) Benchmark
    2. LCCC (Large-scale Chinese Conversational Corpus)
    3. CODI (Chinese Open-domain Dialogue Dataset)
    4. Weibo Sentiment Analysis Datasets
    5. Chinese Medical Question Answering (QA) Datasets
    6. Zhihu
    7. Douban

    AI recommended 7 alternatives but never named chatopera/efaqa-corpus-zh. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a multi-turn dialogue corpus for emotional support NLU model training.
    you: not recommended
    AI recommended (in order):
    1. EmpatheticDialogues
    2. DailyDialog
    3. Persona-Chat
    4. Therapeutic Conversations Corpus
    5. Ubuntu Dialogue Corpus
    6. ConvAI2
    7. MELD

    AI recommended 7 alternatives but never named chatopera/efaqa-corpus-zh. 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 chatopera/efaqa-corpus-zh?
    pass
    AI did not name chatopera/efaqa-corpus-zh — 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 chatopera/efaqa-corpus-zh in production, what risks or prerequisites should they evaluate first?
    pass
    AI named chatopera/efaqa-corpus-zh 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 chatopera/efaqa-corpus-zh solve, and who is the primary audience?
    pass
    AI named chatopera/efaqa-corpus-zh 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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chatopera/efaqa-corpus-zh — 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