RRepoGEO

REPOGEO REPORT · LITE

zhayujie/bot-on-anything

Default branch master · commit 8b448f11 · scanned 5/27/2026, 7:41:52 PM

GitHub: 4,199 stars · 908 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 zhayujie/bot-on-anything, 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 statement to clarify its developer-centric, multi-platform LLM integration focus

    Why:

    CURRENT
    Bot on Anything is a powerful AI chatbot builder that allows you to quickly build chatbots and run them anywhere.
    COPY-PASTE FIX
    Bot on Anything is a powerful developer framework for building and deploying AI chatbots. It provides a unified, lightweight way to connect various large language models (LLMs) like ChatGPT, Claude, and Gemini to diverse applications and messaging platforms (e.g., Telegram, Gmail, Slack, web).
  • mediumtopics#2
    Expand GitHub Topics with broader category terms

    Why:

    CURRENT
    chatgpt, claude, gemini, gmail, slack, telegram, web
    COPY-PASTE FIX
    chatgpt, claude, gemini, gmail, slack, telegram, web, llm-integration, chatbot-framework, multi-platform, ai-agent-builder, developer-tool, python
  • lowreadme#3
    Add a dedicated 'Key Features' or 'Why Bot on Anything?' section to the README

    Why:

    COPY-PASTE FIX
    ## Key Features
- **Unified Framework:** Connects multiple large language models (LLMs) to multiple messaging platforms through a single, abstracted interface.
- **Lightweight Configuration:** Quickly build and run intelligent dialogue robots with minimal setup.
- **High Scalability:** Each application can reuse existing model capabilities, and each new model can run on all application channels.
- **Easy Switching:** Supports easy switching between multiple LLM paths within a single project.

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 zhayujie/bot-on-anything
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Zapier
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Zapier · recommended 1×
  2. Make · recommended 1×
  3. LangChain · recommended 1×
  4. Microsoft Power Automate · recommended 1×
  5. Google Apps Script · recommended 1×
  • CATEGORY QUERY
    How to integrate large language models into various messaging and email applications easily?
    you: not recommended
    AI recommended (in order):
    1. Zapier
    2. Make
    3. LangChain
    4. Microsoft Power Automate
    5. Google Apps Script
    6. OpenAI API
    7. Google AI Studio
    8. Anthropic Claude API

    AI recommended 8 alternatives but never named zhayujie/bot-on-anything. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help deploy custom AI chatbots across different communication and web platforms?
    you: not recommended
    AI recommended (in order):
    1. Botpress
    2. Rasa
    3. Microsoft Bot Framework
    4. Google Cloud Dialogflow (ES/CX)
    5. Amazon Lex
    6. Twilio Autopilot
    7. ManyChat

    AI recommended 7 alternatives but never named zhayujie/bot-on-anything. 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 zhayujie/bot-on-anything?
    pass
    AI named zhayujie/bot-on-anything explicitly

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

  • If a team adopts zhayujie/bot-on-anything in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zhayujie/bot-on-anything 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 zhayujie/bot-on-anything solve, and who is the primary audience?
    pass
    AI did not name zhayujie/bot-on-anything — 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 zhayujie/bot-on-anything. 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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HTML
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zhayujie/bot-on-anything — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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