RRepoGEO

REPOGEO REPORT · LITE

trypear/pearai-master

Default branch main · commit 9eb2f571 · scanned 5/29/2026, 7:17:16 PM

GitHub: 747 stars · 102 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 trypear/pearai-master, 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 to clearly state its purpose

    Why:

    CURRENT
    # PearAI Master Repository

PearAI aims to be an inventory that curates the leading, cutting-edge AI tools in one place. Our unified interface seamlessly integrates these solutions, allowing users to effortlessly switch between tools without needing to waste effort hunting for alternatives.
    COPY-PASTE FIX
    # PearAI: A Unified Interface for Leading AI Coding Assistants

PearAI is a master repository that brings together and integrates the leading, cutting-edge AI coding tools and models into a single, seamless interface. It allows developers to effortlessly switch between powerful AI assistants like ChatGPT, Claude, and others directly within their coding environment, eliminating the need to hunt for alternatives or manage multiple integrations.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Add a `LICENSE` file to the repository root, specifying the chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • mediumtopics#3
    Refine topics to better reflect the 'unified interface' and 'AI tool aggregation' aspects

    Why:

    CURRENT
    ai, ai-code-editor, chatgpt, claude, code-editor, llm, vscode
    COPY-PASTE FIX
    ai, ai-code-editor, chatgpt, claude, code-editor, llm, vscode, ai-assistant-aggregator, unified-ai-interface, developer-tools

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 trypear/pearai-master
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. GitHub Copilot · recommended 1×
  3. Tabnine · recommended 1×
  4. Codeium · recommended 1×
  5. ChatGPT · recommended 1×
  • CATEGORY QUERY
    What are the best code editors that integrate multiple AI coding assistants?
    you: not recommended
    AI recommended (in order):
    1. Visual Studio Code
    2. GitHub Copilot
    3. Tabnine
    4. Codeium
    5. ChatGPT
    6. Google Gemini
    7. JetBrains IDEs
    8. JetBrains AI Assistant
    9. Cursor
    10. OpenAI
    11. Anthropic
    12. NeoVim/Vim
    13. copilot.vim
    14. llm.nvim
    15. Sublime Text

    AI recommended 15 alternatives but never named trypear/pearai-master. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I integrate various large language models into my coding environment for development?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Hugging Face Transformers
    4. OpenAI Python Library
    5. Google Cloud Vertex AI SDK for Python
    6. Anthropic Python SDK

    AI recommended 6 alternatives but never named trypear/pearai-master. 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 trypear/pearai-master?
    pass
    AI did not name trypear/pearai-master — 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 trypear/pearai-master in production, what risks or prerequisites should they evaluate first?
    pass
    AI named trypear/pearai-master 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 trypear/pearai-master solve, and who is the primary audience?
    pass
    AI did not name trypear/pearai-master — 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 trypear/pearai-master. 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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  • Brand-free category queries5 vs 2 in Lite
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