RRepoGEO

REPOGEO REPORT · LITE

dense-analysis/neural

Default branch main · commit 41bc347f · scanned 6/7/2026, 5:26:53 AM

GitHub: 512 stars · 21 forks

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 dense-analysis/neural, 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 opening paragraph for clarity

    Why:

    CURRENT
    # ⚡ Neural

A Neovim/Vim coding agent plugin. Neural integrates various machine learning tools so you can let AI write code for you in Neovim/Vim, among other helpful things.
    COPY-PASTE FIX
    # ⚡ Neural: AI Code Generation Plugin for Vim/Neovim

Neural is a powerful Neovim/Vim coding agent plugin that integrates various machine learning tools, allowing you to leverage AI for code generation, explanation, and more, directly within your editor. It brings the capabilities of OpenAI's APIs (like those powering ChatGPT) and other local models right into your Vim or Neovim workflow.
  • highabout#2
    Add homepage URL to About section

    Why:

    COPY-PASTE FIX
    https://github.com/dense-analysis/neural
  • mediumtopics#3
    Add specific plugin topics

    Why:

    CURRENT
    ai, chatgpt, code-generation, gpt-3, linux, llm, lua, lua-plugin, machine-learning, macos, neovim, openai, python, vim, windows
    COPY-PASTE FIX
    ai, chatgpt, code-generation, gpt-3, linux, llm, lua, lua-plugin, machine-learning, macos, neovim, neovim-plugin, openai, python, vim, vim-plugin, windows

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 dense-analysis/neural
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Tabnine
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Tabnine · recommended 2×
  2. Copilot.vim · recommended 1×
  3. nvim-cmp · recommended 1×
  4. cmp-copilot · recommended 1×
  5. cmp-tabnine · recommended 1×
  • CATEGORY QUERY
    How can I integrate AI code generation and explanation directly into my Neovim workflow?
    you: not recommended
    AI recommended (in order):
    1. Copilot.vim
    2. nvim-cmp
    3. cmp-copilot
    4. cmp-tabnine
    5. Tabnine
    6. CodeGPT.nvim
    7. ChatGPT.nvim
    8. LLM.nvim
    9. vim-ai

    AI recommended 9 alternatives but never named dense-analysis/neural. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best text editor plugins for AI-powered code completion and content generation?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot
    2. Tabnine
    3. CodeWhisperer
    4. Jedi
    5. IntelliCode
    6. Kite

    AI recommended 6 alternatives but never named dense-analysis/neural. 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 dense-analysis/neural?
    pass
    AI named dense-analysis/neural explicitly

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

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

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

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dense-analysis/neural — 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