RRepoGEO

REPOGEO REPORT · LITE

harleyszhang/cv_note

Default branch master · commit 80820e4c · scanned 6/27/2026, 12:42:49 PM

GitHub: 2,630 stars · 390 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 harleyszhang/cv_note, 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 and update description to highlight the inference framework course

    Why:

    CURRENT
    Description: "记录cv算法工程师的成长之路，分享计算机视觉和模型压缩部署技术栈笔记。https://harleyszhang.github.io/cv_note/"
README H1: "<h1 align=\"center\">CV 算法工程师成长之路</h1>"
    COPY-PASTE FIX
    Description: "手把手教你从0到1实现大模型推理框架，并分享计算机视觉算法工程师成长之路、模型压缩部署技术栈笔记和面试题。https://harleyszhang.github.io/cv_note/"
README H1: "<h1 align=\"center\">大模型推理框架实战与CV算法工程师成长笔记</h1>"
  • mediumtopics#2
    Add specific topics related to large model inference and GPU acceleration

    Why:

    CURRENT
    computer-vision, cpp11, deep-learning, interview-questions, machine-learning-algorithms, python3
    COPY-PASTE FIX
    computer-vision, cpp11, deep-learning, interview-questions, machine-learning-algorithms, python3, large-language-models, llm-inference, gpu-acceleration, triton, pytorch-inference
  • lowhomepage#3
    Add the project's main URL to the homepage field

    Why:

    COPY-PASTE FIX
    https://harleyszhang.github.io/cv_note/

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 harleyszhang/cv_note
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 2×
  2. NVIDIA TensorRT · recommended 1×
  3. OpenVINO Toolkit · recommended 1×
  4. ONNX Runtime · recommended 1×
  5. TensorFlow Lite · recommended 1×
  • CATEGORY QUERY
    Seeking guidance to implement efficient deep learning inference frameworks with GPU acceleration.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA TensorRT
    2. OpenVINO Toolkit
    3. ONNX Runtime
    4. PyTorch
    5. TensorFlow Lite
    6. TVM

    AI recommended 6 alternatives but never named harleyszhang/cv_note. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the essential resources for a computer vision engineer preparing for interviews?
    you: not recommended
    AI recommended (in order):
    1. OpenCV
    2. PyTorch
    3. TensorFlow
    4. Keras
    5. LeetCode
    6. HackerRank
    7. arXiv
    8. Papers With Code

    AI recommended 8 alternatives but never named harleyszhang/cv_note. 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 harleyszhang/cv_note?
    pass
    AI named harleyszhang/cv_note explicitly

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

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

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

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harleyszhang/cv_note — 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