RRepoGEO

REPOGEO REPORT · LITE

zixian2021/AI-interview-cards

Default branch main · commit 10557f3e · scanned 5/15/2026, 7:32:30 PM

GitHub: 1,343 stars · 120 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 zixian2021/AI-interview-cards, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai, machine-learning, deep-learning, interview-questions, interview-prep, llm, nlp, computer-vision, data-science, algorithms, python
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with your chosen license (e.g., MIT, Apache-2.0) to clarify usage rights.
  • highreadme#3
    Reposition the README H1 to clearly state the repo's purpose

    Why:

    CURRENT
    # 2023.8.13更新:
    COPY-PASTE FIX
    # AI Interview Cards: 最完整的AI算法面试题目仓库，1000道，25个类目

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 zixian2021/AI-interview-cards
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 (Machine Learning Edition) · recommended 1×
  3. Machine Learning Interviews by Chip Huyen · recommended 1×
  4. Glassdoor · recommended 1×
  5. Towards Data Science (Medium) · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive interview questions and answers for machine learning roles?
    you: not recommended
    AI recommended (in order):
    1. Cracking the Coding Interview (Machine Learning Edition)
    2. Machine Learning Interviews by Chip Huyen
    3. Glassdoor
    4. LeetCode
    5. Towards Data Science (Medium)
    6. Awesome Machine Learning Interview
    7. The Hundred-Page Machine Learning Book by Andriy Burkov

    AI recommended 7 alternatives but never named zixian2021/AI-interview-cards. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for advanced deep learning and LLM interview preparation materials with Q&A.
    you: not recommended
    AI recommended (in order):
    1. Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI
    2. Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
    3. Dive into Deep Learning
    4. The Hundred-Page Machine Learning Book
    5. Machine Learning Engineering for Production (MLOps) Specialization
    6. Attention Is All You Need
    7. LeetCode
    8. HackerRank

    AI recommended 8 alternatives but never named zixian2021/AI-interview-cards. 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 zixian2021/AI-interview-cards?
    pass
    AI did not name zixian2021/AI-interview-cards — 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 zixian2021/AI-interview-cards in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zixian2021/AI-interview-cards 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 zixian2021/AI-interview-cards solve, and who is the primary audience?
    pass
    AI did not name zixian2021/AI-interview-cards — 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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zixian2021/AI-interview-cards — 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