REPOGEO REPORT · LITE

AI-QL/tuui

Default branch main · commit 0be51344 · scanned 5/21/2026, 10:31:21 PM

GitHub: 1,147 stars · 105 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 AI-QL/tuui, 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 "TUUI" is a graphical desktop app, not a TUI

Why:

CURRENT

#### TUUI is a desktop MCP client designed as a tool unitary utility integration, accelerating AI adoption through the Model Context Protocol (MCP) and enabling cross-vendor LLM API orchestration.

COPY-PASTE FIX

#### TUUI is a graphical desktop application (not a terminal user interface, or TUI) and an MCP client designed as a tool unitary utility integration, accelerating AI adoption through the Model Context Protocol (MCP) and enabling cross-vendor LLM API orchestration.

mediumtopics#2

Add specific topics for desktop GUI LLM clients

Why:

CURRENT

agent, agentic-ai, ai, ai-playground, anthropic, claude, deepseek, dxt, llm, llm-eval, mcp, mcp-client, mcp-host, mcp-inspector, mcpb, model-context-protocol, openai-api, prompt, qwen, testing

COPY-PASTE FIX

agent, agentic-ai, ai, ai-playground, anthropic, claude, deepseek, dxt, llm, llm-eval, mcp, mcp-client, mcp-host, mcp-inspector, mcpb, model-context-protocol, openai-api, prompt, qwen, testing, desktop-app, gui, local-llm, llm-client

mediumreadme#3

Expand README intro to highlight "local AI playground" and "prompt engineering"

Why:

CURRENT

This repository is essentially an **LLM chat desktop application based on MCP**. It also represents a bold experiment in **creating a complete project using AI**.

COPY-PASTE FIX

This repository is essentially an **LLM chat desktop application based on MCP**, serving as a powerful local AI playground for prompt engineering, LLM development, and cross-vendor model testing. It also represents a bold experiment in **creating a complete project using AI**.

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 AI-QL/tuui

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

LM Studio

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

LM Studio · recommended 2×
ollama/ollama · recommended 1×
janhq/jan · recommended 1×
mudler/LocalAI · recommended 1×
nomic-ai/gpt4all · recommended 1×

CATEGORY QUERY
What open-source desktop clients allow testing and comparing different large language models?
you: not recommended
AI recommended (in order):
1. LM Studio
2. Ollama (ollama/ollama)
3. Jan (janhq/jan)
4. LocalAI (mudler/LocalAI)
5. GPT4All (nomic-ai/gpt4all)
AI recommended 5 alternatives but never named AI-QL/tuui. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How to set up a local AI playground for prompt engineering and LLM development?
you: not recommended
AI recommended (in order):
1. LM Studio
2. Ollama
3. Jan
4. LocalAI
5. text-generation-webui (Oobabooga)
6. Hugging Face Transformers
7. Llama.cpp
8. llama-cpp-python
AI recommended 8 alternatives but never named AI-QL/tuui. 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 AI-QL/tuui?
pass
AI named AI-QL/tuui explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts AI-QL/tuui in production, what risks or prerequisites should they evaluate first?
pass
AI named AI-QL/tuui 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 AI-QL/tuui solve, and who is the primary audience?
pass
AI named AI-QL/tuui 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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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/AI-QL/tuui.svg)](https://repogeo.com/en/r/AI-QL/tuui)

HTML

<a href="https://repogeo.com/en/r/AI-QL/tuui"><img src="https://repogeo.com/badge/AI-QL/tuui.svg" alt="RepoGEO" /></a>

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AI-QL/tuui — 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