RRepoGEO

REPOGEO REPORT · LITE

Chevey339/kelivo

Default branch master · commit c2eccb22 · scanned 5/16/2026, 4:27:36 AM

GitHub: 2,626 stars · 249 forks

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 Chevey339/kelivo, 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 strong introductory sentence to the README to clarify project type and maturity

    Why:

    CURRENT
    A Flutter LLM Chat Client
    COPY-PASTE FIX
    A robust, production-ready cross-platform Flutter application providing a feature-rich chat client for various Large Language Models (LLMs), designed for both mobile and desktop environments.
  • highabout#2
    Enhance the repository description for clarity and detail

    Why:

    CURRENT
    A Flutter LLM Chat Client. Support Mobile & Desktop.
    COPY-PASTE FIX
    Kelivo is a feature-rich, cross-platform Flutter application for interacting with various Large Language Models (LLMs), offering multimodal input, custom assistants, and multi-provider support on mobile and desktop.
  • mediumreadme#3
    Add a 'Why Kelivo?' or 'Key Differentiators' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, e.g., '## ✨ Why Choose Kelivo?' or '## 🚀 Key Differentiators', and list 2-3 unique selling points, such as:

Kelivo stands out as a complete, ready-to-use application, not just a library. It offers:
- **Comprehensive Multi-provider Support:** Seamlessly integrate with OpenAI, Google Gemini, Anthropic, and more.
- **Advanced Multimodal Input:** Go beyond text with support for images, PDFs, and Word documents.
- **Full Cross-Platform Experience:** A consistent, modern Material You design across Android, iOS, HarmonyOS, Windows, macOS, and Linux.

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 Chevey339/kelivo
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
FlutterFlow
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. FlutterFlow · recommended 1×
  2. Riverpod · recommended 1×
  3. flutter_hooks · recommended 1×
  4. go_router · recommended 1×
  5. Bloc · recommended 1×
  • CATEGORY QUERY
    How to implement a cross-platform chat client for large language models with Flutter?
    you: not recommended
    AI recommended (in order):
    1. FlutterFlow
    2. Riverpod
    3. flutter_hooks
    4. go_router
    5. Bloc
    6. flutter_bloc
    7. Provider
    8. GetX
    9. http package
    10. dio package

    AI recommended 10 alternatives but never named Chevey339/kelivo. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Are there any Flutter-based LLM chat applications supporting multiple AI providers and multimodal input?
    you: not recommended
    AI recommended (in order):
    1. flutter_gemini
    2. openai_dart
    3. http
    4. dio
    5. image_picker
    6. file_picker
    7. audio_recorder
    8. just_audio
    9. provider
    10. riverpod
    11. bloc
    12. dash_chat_2
    13. flutter_chat_ui
    14. langchain_dart

    AI recommended 14 alternatives but never named Chevey339/kelivo. 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 Chevey339/kelivo?
    pass
    AI named Chevey339/kelivo explicitly

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

  • If a team adopts Chevey339/kelivo in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Chevey339/kelivo 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 Chevey339/kelivo solve, and who is the primary audience?
    pass
    AI named Chevey339/kelivo explicitly

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

Embed your GEO score

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Chevey339/kelivo — 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