RRepoGEO

REPOGEO REPORT · LITE

hanshuaikang/nezha

Default branch main · commit 11333ffb · scanned 6/27/2026, 9:36:53 PM

GitHub: 1,722 stars · 169 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
40 /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
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 hanshuaikang/nezha, 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 prominent English positioning statement to the README

    Why:

    COPY-PASTE FIX
    Add the following text prominently at the top of `README.md`, ideally right after the main title/badges: 'Nezha is a lightweight, cross-platform IDE specifically designed for the AI Agents Era, enabling you to run and manage multiple Claude Code and Codex agents across various projects.'
  • mediumreadme#2
    Translate or summarize the 'Why Nezha' section into English in the main README

    Why:

    COPY-PASTE FIX
    Add an English section titled 'Why Nezha' (or similar) directly into the main `README.md`, explaining the core problem Nezha solves for AI-driven development and its differentiators from traditional IDEs. This should be a concise translation or summary of the existing Chinese section.
  • lowtopics#3
    Add more specific topics for AI agent development

    Why:

    CURRENT
    ai, claude-code, codex, cursor, ide, vibe-coding, vibecoding
    COPY-PASTE FIX
    ai, claude-code, codex, cursor, ide, vibe-coding, vibecoding, ai-agent-ide, multi-agent-development, ai-coding-assistant

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 hanshuaikang/nezha
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Visual Studio Code
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Visual Studio Code · recommended 1×
  2. JetBrains PyCharm · recommended 1×
  3. JetBrains IntelliJ IDEA · recommended 1×
  4. Eclipse IDE · recommended 1×
  5. JupyterLab · recommended 1×
  • CATEGORY QUERY
    Looking for an IDE to efficiently manage multiple AI coding agents across different projects.
    you: not recommended
    AI recommended (in order):
    1. Visual Studio Code
    2. JetBrains PyCharm
    3. JetBrains IntelliJ IDEA
    4. Eclipse IDE
    5. JupyterLab

    AI recommended 5 alternatives but never named hanshuaikang/nezha. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What's a good lightweight IDE for AI-driven development with integrated Git and multi-project support?
    you: not recommended
    AI recommended (in order):
    1. Visual Studio Code (microsoft/vscode)
    2. JupyterLab (jupyterlab/jupyterlab)
    3. Sublime Text
    4. Atom (atom/atom)
    5. Spyder (spyder-ide/spyder)

    AI recommended 5 alternatives but never named hanshuaikang/nezha. 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 hanshuaikang/nezha?
    pass
    AI named hanshuaikang/nezha explicitly

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

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

    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 hanshuaikang/nezha. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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hanshuaikang/nezha — 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