REPOGEO REPORT · LITE

jhc13/taggui

Default branch main · commit cb8cca71 · scanned 5/19/2026, 7:12:05 PM

GitHub: 1,310 stars · 72 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

28 /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

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 jhc13/taggui, 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 H1 and opening paragraph to clarify niche

Why:

CURRENT

# TagGUI

Cross-platform desktop application for quickly adding and editing image tags and captions, aimed towards creators of image datasets for generative AI models.

COPY-PASTE FIX

# TagGUI: Desktop Tag & Caption Manager for Generative AI Datasets

TagGUI is the essential cross-platform desktop application purpose-built for generative AI artists and dataset creators. It provides a fast, keyboard-friendly interface to manage and caption image datasets specifically for training models like Stable Diffusion, offering a streamlined workflow distinct from general image annotation tools or raw AI models.

mediumhomepage#2
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://jhc13.github.io/taggui/
```

lowcomparison#3

Add a 'Why TagGUI?' or 'Comparison' section to the README

Why:

COPY-PASTE FIX

## Why TagGUI?

Unlike general image annotation tools (e.g., LabelImg, CVAT) focused on bounding boxes or segmentation, TagGUI is purpose-built for the unique workflow of generative AI dataset creation, emphasizing rapid text-based tagging and captioning. It also integrates, rather than replaces, powerful AI models like CLIP or BLIP for automated suggestions, providing a complete desktop solution that streamlines your dataset preparation.

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 jhc13/taggui

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

tzutalin/labelImg

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

tzutalin/labelImg · recommended 1×
opencv/cvat · recommended 1×
sgothel/via · recommended 1×
heartexlabs/label-studio · recommended 1×
jsbroks/coco-annotator · recommended 1×

CATEGORY QUERY
What's a good desktop tool for quickly tagging and captioning AI image datasets?
you: not recommended
AI recommended (in order):
1. LabelImg (tzutalin/labelImg)
2. CVAT (Computer Vision Annotation Tool) (opencv/cvat)
3. VGG Image Annotator (VIA) (sgothel/via)
4. Label Studio (heartexlabs/label-studio)
5. COCO Annotator (jsbroks/coco-annotator)
6. Darklabel (darklabel-app/darklabel)
AI recommended 6 alternatives but never named jhc13/taggui. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for an application to automatically generate and manage image tags for generative models.
you: not recommended
AI recommended (in order):
1. DeepDanbooru
2. OpenAI's CLIP
3. BLIP
4. Hydrus Network
5. Google Cloud Vision AI
6. Amazon Rekognition
AI recommended 6 alternatives but never named jhc13/taggui. 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 jhc13/taggui?
pass
AI did not name jhc13/taggui — 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 jhc13/taggui in production, what risks or prerequisites should they evaluate first?
pass
AI named jhc13/taggui 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 jhc13/taggui solve, and who is the primary audience?
pass
AI named jhc13/taggui explicitly
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 jhc13/taggui. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/jhc13/taggui.svg)](https://repogeo.com/en/r/jhc13/taggui)

HTML

<a href="https://repogeo.com/en/r/jhc13/taggui"><img src="https://repogeo.com/badge/jhc13/taggui.svg" alt="RepoGEO" /></a>

Pro

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jhc13/taggui — 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