RRepoGEO

REPOGEO REPORT · LITE

datawhalechina/daily-interview

Default branch master · commit f35e8d55 · scanned 5/24/2026, 1:32:44 AM

GitHub: 3,691 stars · 497 forks

AI VISIBILITY SCORE
27 /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
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 datawhalechina/daily-interview, 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 README H1 to highlight its unique format and language

    Why:

    CURRENT
    <h1>⭐Daily Interview - 面试必看 </h1>
    **每一个面试者面试之前必看一遍的小面经**
    COPY-PASTE FIX
    <h1>⭐Daily Interview - 精选高频面试笔记 (中文)</h1>
    <p><strong>Datawhale 社区成员整理的中文面试笔记,涵盖机器学习、CV、NLP、推荐、开发等高频考点,助你快速复习。</strong></p>
  • mediumtopics#2
    Add more specific and descriptive topics

    Why:

    CURRENT
    cv, interview-questions, llm, nlp
    COPY-PASTE FIX
    interview-prep, machine-learning, deep-learning, computer-vision, natural-language-processing, recommendation-systems, software-development, data-science, chinese-language, study-notes, high-frequency-questions
  • mediumcomparison#3
    Add a 'Why Daily Interview?' section comparing it to common alternatives

    Why:

    COPY-PASTE FIX
    ## 💡 为什么选择 Daily Interview?
    
    市面上有许多优秀的面试资源,如 LeetCode、牛客网、各类面试书籍(如《剑指 Offer》、《Cracking the Coding Interview》)。Daily Interview 的独特之处在于:
    
    - **精选与聚焦**:我们不追求题库的广度,而是专注于整理面试中最高频、最核心的知识点和题目,助你高效复习。
    - **笔记形式**:以简洁明了的笔记形式呈现,方便快速阅读和理解,而非需要大量练习的编程平台。
    - **中文内容**:所有内容均由 Datawhale 社区成员精心整理,更贴近中文面试环境和习惯。
    - **持续更新**:社区驱动,内容会根据技术发展和面试趋势持续更新。

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 datawhalechina/daily-interview
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LeetCode
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LeetCode · recommended 2×
  2. Cracking the Coding Interview (CTCI) · recommended 1×
  3. Grokking the Machine Learning Interview · recommended 1×
  4. Designing Machine Learning Systems · recommended 1×
  5. Towards Data Science (Medium) · recommended 1×
  • CATEGORY QUERY
    What are essential resources for quickly reviewing high-frequency machine learning interview questions?
    you: not recommended
    AI recommended (in order):
    1. Cracking the Coding Interview (CTCI)
    2. Grokking the Machine Learning Interview
    3. Designing Machine Learning Systems
    4. LeetCode
    5. Towards Data Science (Medium)
    6. The Hundred-Page Machine Learning Book
    7. Glassdoor
    8. Blind

    AI recommended 8 alternatives but never named datawhalechina/daily-interview. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find concise interview preparation materials for AI and software development roles?
    you: not recommended
    AI recommended (in order):
    1. LeetCode
    2. Cracking the Coding Interview (CTCI) by Gayle Laakmann McDowell
    3. NeetCode.io
    4. Grokking the System Design Interview
    5. AlgoExpert.io
    6. Interview Cake
    7. Machine Learning Interview Questions (various GitHub repos)

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

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datawhalechina/daily-interview — 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