RRepoGEO

REPOGEO REPORT · LITE

xu-xiang/everything-claude-code-zh

Default branch main · commit dfbf9467 · scanned 6/9/2026, 12:37:52 PM

GitHub: 1,045 stars · 183 forks

AI VISIBILITY SCORE
33 /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
2 / 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 xu-xiang/everything-claude-code-zh, 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 the README's opening paragraph to clarify its role as a production-grade configuration system

    Why:

    CURRENT
    为 AI 智能体（Agent）框架打造的性能优化系统。
    COPY-PASTE FIX
    **Everything Claude Code** 是一个源自 Anthropic 黑客松获胜作品的**生产级 AI 智能体配置与模式集合**，为 **Claude Code, Codex, Cowork** 及其他 AI 智能体框架提供完整的系统优化方案。它包含实战验证的 Agents, Skills, Hooks, Commands, Rules 和 MCPs，旨在帮助中文工程师高效构建和部署高性能 AI 智能体。
  • mediumabout#2
    Refine the repository description to emphasize 'production-grade system'

    Why:

    CURRENT
    everything-claude-code 中文翻译项目：完整的 Claude Code 配置集合（agents, skills, hooks, commands, rules, MCPs）。源自 Anthropic 黑客松获胜者的实战配置，助力中文工程师高效理解与使用 Claude Code。
    COPY-PASTE FIX
    everything-claude-code 中文翻译项目：一个**生产级、实战验证的 Claude Code AI 智能体完整配置系统**（包含 agents, skills, hooks, commands, rules, MCPs）。源自 Anthropic 黑客松获胜者的实战配置，助力中文工程师高效理解与使用 Claude Code。
  • mediumtopics#3
    Add more specific topics to highlight 'production-grade' and 'system' aspects

    Why:

    CURRENT
    ai-agents, anthropic, claude, claude-code, developer-tools, everything-claude-code, llm, mcp, oneskill, productivity
    COPY-PASTE FIX
    ai-agents, anthropic, claude, claude-code, developer-tools, everything-claude-code, llm, mcp, oneskill, productivity, ai-agent-patterns, ai-agent-configurations, production-ai, ai-system-design

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 xu-xiang/everything-claude-code-zh
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. Microsoft Semantic Kernel · recommended 1×
  4. AutoGPT · recommended 1×
  5. BabyAGI · recommended 1×
  • CATEGORY QUERY
    Where can I find production-grade configurations and a complete system for AI agent development?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Microsoft Semantic Kernel
    4. AutoGPT
    5. BabyAGI
    6. Haystack

    AI recommended 6 alternatives but never named xu-xiang/everything-claude-code-zh. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to build robust AI agents using pre-configured skills, hooks, and commands efficiently?
    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. Haystack (deepset-ai/haystack)
    5. AutoGPT (Significant-Gravitas/AutoGPT)
    6. BabyAGI (yoheinakajima/babyagi)
    7. CrewAI (joaomdmoura/crewai)
    8. OpenAI Assistants API

    AI recommended 8 alternatives but never named xu-xiang/everything-claude-code-zh. 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 xu-xiang/everything-claude-code-zh?
    pass
    AI named xu-xiang/everything-claude-code-zh explicitly

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

  • If a team adopts xu-xiang/everything-claude-code-zh in production, what risks or prerequisites should they evaluate first?
    pass
    AI named xu-xiang/everything-claude-code-zh 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 xu-xiang/everything-claude-code-zh solve, and who is the primary audience?
    pass
    AI did not name xu-xiang/everything-claude-code-zh — 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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