RRepoGEO

REPOGEO REPORT · LITE

qiuhuachuan/smile

Default branch main · commit 9f8afc0b · scanned 6/6/2026, 12:07:35 AM

GitHub: 528 stars · 57 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 qiuhuachuan/smile, 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
    Add a concise introductory sentence to the README

    Why:

    COPY-PASTE FIX
    # 中文心理健康支持对话 · 数据集(SmileChat)与大模型(MeChat)

This repository presents MeChat, a large language model, and SmileChat, a dataset, specifically designed for mental health support dialogue in Chinese.

## 🎉🎉🎉 accepted to the EMNLP 2024 Findings
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    chinese-nlp, mental-health, chatbot, large-language-model, llm, nlp, dataset, emnlp-2024
  • mediumreadme#3
    Correct the broken paper link in the README

    Why:

    CURRENT
    <a href='https://aclanthology.org/2024.findings-emnlp.34/'></a>
    COPY-PASTE FIX
    <a href='https://aclanthology.org/2024.findings-emnlp.34/'>Paper Link</a>

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 qiuhuachuan/smile
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ERNIE Bot
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ERNIE Bot · recommended 1×
  2. SenseChat · recommended 1×
  3. Qwen · recommended 1×
  4. GLM-4 · recommended 1×
  5. GPT-4 · recommended 1×
  • CATEGORY QUERY
    What large language models are available for developing Chinese mental health support chatbots?
    you: not recommended
    AI recommended (in order):
    1. ERNIE Bot
    2. SenseChat
    3. Qwen
    4. GLM-4
    5. GPT-4
    6. Llama 3

    AI recommended 6 alternatives but never named qiuhuachuan/smile. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I implement an AI assistant for confidential and empathetic psychological support in Chinese?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. Google Gemini
    3. Hugging Face Transformers
    4. Baidu ERNIE Bot
    5. Microsoft Azure OpenAI Service
    6. Anthropic Claude
    7. Llama 2
    8. Mistral

    AI recommended 8 alternatives but never named qiuhuachuan/smile. 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 qiuhuachuan/smile?
    pass
    AI named qiuhuachuan/smile explicitly

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

  • If a team adopts qiuhuachuan/smile in production, what risks or prerequisites should they evaluate first?
    pass
    AI named qiuhuachuan/smile 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 qiuhuachuan/smile solve, and who is the primary audience?
    pass
    AI named qiuhuachuan/smile explicitly

    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 qiuhuachuan/smile. 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/qiuhuachuan/smile.svg)](https://repogeo.com/en/r/qiuhuachuan/smile)
HTML
<a href="https://repogeo.com/en/r/qiuhuachuan/smile"><img src="https://repogeo.com/badge/qiuhuachuan/smile.svg" alt="RepoGEO" /></a>
Pro

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qiuhuachuan/smile — 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