RRepoGEO

REPOGEO REPORT · LITE

mylxsw/cc-src-learning

Default branch main · commit a21562c9 · scanned 6/27/2026, 10:39:16 AM

GitHub: 501 stars · 133 forks

AI VISIBILITY SCORE
22 /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
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 mylxsw/cc-src-learning, 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 explicitly state repo name and clarify subject

    Why:

    CURRENT
    # 透过 Claude Code 的源码，我们学到了什么？
    COPY-PASTE FIX
    # mylxsw/cc-src-learning: Claude Code 源码深度解析与 AI 工程实践学习
  • hightopics#2
    Expand topics to include AI engineering and analysis keywords

    Why:

    CURRENT
    claude, claude-code
    COPY-PASTE FIX
    claude, claude-code, ai-engineering, ai-design-patterns, agent-systems, prompt-engineering, source-code-analysis, reverse-engineering, llm-applications, ai-tools
  • mediumhomepage#3
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/mylxsw/cc-src-learning

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 mylxsw/cc-src-learning
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google AI Blog
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google AI Blog · recommended 1×
  2. AWS Machine Learning Blog · recommended 1×
  3. Microsoft Azure AI Blog · recommended 1×
  4. Papers With Code · recommended 1×
  5. Netflix Technology Blog · recommended 1×
  • CATEGORY QUERY
    How to learn best practices for building robust AI applications from real-world examples?
    you: not recommended
    AI recommended (in order):
    1. Google AI Blog
    2. AWS Machine Learning Blog
    3. Microsoft Azure AI Blog
    4. Papers With Code
    5. Netflix Technology Blog
    6. Towards Data Science
    7. Hugging Face Blog
    8. Transformers library

    AI recommended 8 alternatives but never named mylxsw/cc-src-learning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective design patterns for AI agent tool systems and plugin architectures?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    4. OpenAPI Specification (OAI/OpenAPI-Specification)
    5. JSON Schema (json-schema-org/json-schema-spec)

    AI recommended 5 alternatives but never named mylxsw/cc-src-learning. 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 mylxsw/cc-src-learning?
    pass
    AI did not name mylxsw/cc-src-learning — 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 mylxsw/cc-src-learning in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mylxsw/cc-src-learning 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 mylxsw/cc-src-learning solve, and who is the primary audience?
    pass
    AI did not name mylxsw/cc-src-learning — 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

Drop this badge into the README of mylxsw/cc-src-learning. 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/mylxsw/cc-src-learning.svg)](https://repogeo.com/en/r/mylxsw/cc-src-learning)
HTML
<a href="https://repogeo.com/en/r/mylxsw/cc-src-learning"><img src="https://repogeo.com/badge/mylxsw/cc-src-learning.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

mylxsw/cc-src-learning — 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