REPOGEO REPORT · LITE

patrickjohncyh/fashion-clip

Default branch master · commit 0b4b4f9c · scanned 6/6/2026, 12:02:45 AM

GitHub: 518 stars · 55 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 patrickjohncyh/fashion-clip, 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 concise introductory paragraph to the README

Why:

CURRENT

The README currently starts with links and a 'Quick Start' section immediately after the title.

COPY-PASTE FIX

Add the following paragraph directly after the `# FashionCLIP` title:
`FashionCLIP is a specialized vision-language model fine-tuned specifically for the fashion domain, building upon the robust architecture of CLIP. It provides highly accurate multi-modal embeddings for fashion items, enabling advanced applications like semantic product search, recommendation systems, and detailed item classification within e-commerce and retail.`

mediumhomepage#2

Add a homepage URL to the repository metadata

Why:

COPY-PASTE FIX

Set the repository homepage URL to `https://huggingface.co/patrickjohncyh/fashion-clip` (or the most appropriate project page if different).

lowreadme#3

Explicitly list key use cases in the README

Why:

CURRENT

Use cases are implied but not explicitly listed in a dedicated section near the top.

COPY-PASTE FIX

Add a 'Key Use Cases' section after the introduction, listing:
`## Key Use Cases`
`- Semantic Fashion Product Search`
`- Multi-modal Fashion Item Retrieval`
`- Zero-shot Fashion Item Classification`
`- Fashion Recommendation Systems`
`- E-commerce Visual Search`

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 patrickjohncyh/fashion-clip

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

huggingface/transformers

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

huggingface/transformers · recommended 1×
facebookresearch/faiss · recommended 1×
pytorch/pytorch · recommended 1×
tensorflow/tensorflow · recommended 1×
openai/CLIP · recommended 1×

CATEGORY QUERY
How to build better fashion product search using multi-modal embeddings?
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers (huggingface/transformers)
2. FAISS (facebookresearch/faiss)
3. PyTorch (pytorch/pytorch)
4. TensorFlow (tensorflow/tensorflow)
5. OpenAI CLIP (openai/CLIP)
6. Pinecone
7. Weaviate (weaviate/weaviate)
8. Jina AI (jina-ai/jina)
9. Milvus (milvus-io/milvus)
10. Google Cloud Vertex AI Matching Engine
11. Amazon OpenSearch Service
AI recommended 11 alternatives but never named patrickjohncyh/fashion-clip. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a specialized vision-language model for accurate fashion item classification and retrieval.
you: not recommended
AI recommended (in order):
1. CLIP
2. FashionCLIP
3. BLIP
4. OpenCLIP
5. Florence-2
6. ViT-L/14@336px
AI recommended 6 alternatives but never named patrickjohncyh/fashion-clip. 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 patrickjohncyh/fashion-clip?
pass
AI named patrickjohncyh/fashion-clip explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts patrickjohncyh/fashion-clip in production, what risks or prerequisites should they evaluate first?
pass
AI named patrickjohncyh/fashion-clip 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 patrickjohncyh/fashion-clip solve, and who is the primary audience?
pass
AI named patrickjohncyh/fashion-clip 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)

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HTML

<a href="https://repogeo.com/en/r/patrickjohncyh/fashion-clip"><img src="https://repogeo.com/badge/patrickjohncyh/fashion-clip.svg" alt="RepoGEO" /></a>

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patrickjohncyh/fashion-clip — 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