RRepoGEO

REPOGEO REPORT · LITE

openedclaude/claude-reviews-claude

Default branch main · commit a52d83b7 · scanned 6/24/2026, 4:03:01 AM

GitHub: 1,513 stars · 697 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)

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

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 openedclaude/claude-reviews-claude, 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
    Add a direct, descriptive subtitle to the README's main heading

    Why:

    CURRENT
    # 🪞 Claude 眼中的老己
### *Claude Reviews Claude Code —— 当局者清*
    COPY-PASTE FIX
    # 🪞 Claude 眼中的老己
### *Claude Reviews Claude Code —— 当局者清*

**一份由 Claude 撰写的、关于 Claude Code v2.1.88 的17章架构深度分析文档。**
  • mediumtopics#2
    Add more specific topics related to documentation and analysis

    Why:

    CURRENT
    agent, agentic-ai, ai, anthropic, architecture, claude, claude-code, deep-dive, documentation, llm, meta, reverse-engineering, source-code, typescript, vibe-coding
    COPY-PASTE FIX
    agent-architecture, agent-system-analysis, ai-documentation, llm-architecture, code-analysis, technical-documentation, reverse-engineering, source-code-analysis, deep-dive, claude, anthropic, typescript, llm, ai, meta, vibe-coding
  • lowreadme#3
    Add a 'What this is NOT' section to the README

    Why:

    COPY-PASTE FIX
    ## 💡 这不是什么？

本项目**不是**一个可运行的 AI 代理框架（如 Auto-GPT 或 BabyAGI），也**不是**一个代码生成或文档工具（如 GitHub Copilot 或 TypeDoc）。它是一份由 AI 撰写的、关于另一个 AI 内部架构的**静态分析报告**。

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 openedclaude/claude-reviews-claude
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Auto-GPT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Auto-GPT · recommended 1×
  2. BabyAGI · recommended 1×
  3. LangChain Agents · recommended 1×
  4. GitHub · recommended 1×
  5. VS Code · recommended 1×
  • CATEGORY QUERY
    How can I understand the internal architecture of a complex LLM agent system?
    you: not recommended
    AI recommended (in order):
    1. Auto-GPT
    2. BabyAGI
    3. LangChain Agents
    4. GitHub
    5. VS Code
    6. draw.io
    7. diagrams.net
    8. Lucidchart
    9. Mermaid
    10. Python's `pdb`
    11. VS Code Debugger
    12. LangChain's LangSmith
    13. LlamaIndex's Observability Features

    AI recommended 13 alternatives but never named openedclaude/claude-reviews-claude. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find examples of AI systems documenting their own TypeScript codebase?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot
    2. Tabnine
    3. Codeium
    4. TypeDoc (TypeStrong/TypeDoc)
    5. Documatic
    6. Swimm
    7. Hugging Face Models
    8. CodeLlama
    9. GPT-4 variants

    AI recommended 9 alternatives but never named openedclaude/claude-reviews-claude. 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 openedclaude/claude-reviews-claude?
    pass
    AI named openedclaude/claude-reviews-claude explicitly

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

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