RRepoGEO

REPOGEO REPORT · LITE

Vali-98/ChatterUI

Default branch master · commit 839dab24 · scanned 5/27/2026, 12:37:31 PM

GitHub: 2,438 stars · 213 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 Vali-98/ChatterUI, 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
    Clarify README's opening to explicitly state what ChatterUI is and is not

    Why:

    CURRENT
    ChatterUI is a native mobile frontend for LLMs.
    COPY-PASTE FIX
    ChatterUI is a dedicated native mobile frontend for Large Language Models (LLMs), designed specifically for on-device inference or connecting to various LLM APIs. It is *not* a generic chat UI component library focused on styling, but a full application for interacting with LLMs.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    react-native, llm, large-language-models, on-device-ai, mobile-ai, chat-ui, character-ai, llama-cpp, gguf
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/Vali-98/ChatterUI

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 Vali-98/ChatterUI
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
React Native
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. React Native · recommended 1×
  2. react-native-gifted-chat · recommended 1×
  3. Flutter · recommended 1×
  4. SwiftUI · recommended 1×
  5. Jetpack Compose · recommended 1×
  • CATEGORY QUERY
    What are the best mobile UI frameworks for building custom LLM chat applications?
    you: not recommended
    AI recommended (in order):
    1. React Native
    2. react-native-gifted-chat
    3. Flutter
    4. SwiftUI
    5. Jetpack Compose
    6. Ionic
    7. NativeScript

    AI recommended 7 alternatives but never named Vali-98/ChatterUI. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I integrate on-device LLMs or external APIs into a React Native mobile app?
    you: not recommended
    AI recommended (in order):
    1. Axios (axios/axios)
    2. Fetch API
    3. react-query (TanStack/query)
    4. swr (vercel/swr)
    5. react-native-pytorch-core (pytorch/react-native-pytorch-core)
    6. react-native-tflite-react-native (shaon07/react-native-tflite-react-native)
    7. Core ML
    8. ML Kit
    9. OpenAI SDK (openai/openai-node)
    10. Hugging Face transformers.js (xenova/transformers.js)

    AI recommended 10 alternatives but never named Vali-98/ChatterUI. 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 Vali-98/ChatterUI?
    pass
    AI named Vali-98/ChatterUI explicitly

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

  • If a team adopts Vali-98/ChatterUI in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Vali-98/ChatterUI 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 Vali-98/ChatterUI solve, and who is the primary audience?
    pass
    AI named Vali-98/ChatterUI explicitly

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

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Vali-98/ChatterUI — 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