REPOGEO REPORT · LITE

StarTrail-org/PixelRAG

Default branch main · commit 6d9cdda7 · scanned 6/22/2026, 12:27:06 AM

GitHub: 2,479 stars · 208 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 StarTrail-org/PixelRAG, 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 README opening to emphasize pixel-native web search

Why:

CURRENT

<p align="center">
  
</p>
<p align="center">
  Official codebase for <b><a href="assets/pixelrag-paper.pdf">PIXELRAG: Web Screenshots Beat Text for
Retrieval-Augmented Generation</a></b>
</p>

COPY-PASTE FIX

<p align="center">
  <b>The end of web parsing. The beginning of scalable pixel-native search.</b>
</p>
<p align="center">
  Search any document by how it <em>looks</em>, not just the text it contains.
</p>
<p align="center">
  Official codebase for <b><a href="assets/pixelrag-paper.pdf">PIXELRAG: Web Screenshots Beat Text for
Retrieval-Augmented Generation</a></b>
</p>

mediumtopics#2

Add more specific topics for visual web RAG

Why:

CURRENT

agent, ai, memory, multimodal, rag, search, searchengine, vision, vlm

COPY-PASTE FIX

agent, ai, memory, multimodal, rag, search, searchengine, vision, vlm, web-search, visual-rag, screenshot-search, document-layout

lowreadme#3

Add a 'Comparison' section to the README

Why:

COPY-PASTE FIX

## PixelRAG vs. Traditional RAG & Vector Databases

Unlike traditional RAG systems that rely on parsed text or general vector databases, PixelRAG focuses on pixel-native retrieval from web page screenshots. This allows it to understand visual context, layout, and non-textual information, providing a richer and more accurate retrieval experience for web-based content compared to text-only approaches or generic vector search solutions like LlamaIndex, LangChain, or Weaviate.

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 StarTrail-org/PixelRAG

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Weaviate

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Weaviate · recommended 2×
LlamaIndex · recommended 1×
LangChain · recommended 1×
Pinecone · recommended 1×
Qdrant · recommended 1×

CATEGORY QUERY
How to perform RAG using visual information from web pages instead of just text?
you: not recommended
AI recommended (in order):
1. LlamaIndex
2. LangChain
3. Pinecone
4. Weaviate
5. Qdrant
6. Milvus
7. Hugging Face Transformers
8. CLIP
9. ViT
10. YOLOv8
11. Google Cloud Vision AI
12. Azure Cognitive Services
13. Google Cloud Vertex AI
14. Azure OpenAI Service
15. Google Cloud Matching Engine
16. OpenAI's GPT-4V
17. Weaviate
18. img2vec-clip
AI recommended 18 alternatives but never named StarTrail-org/PixelRAG. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a search engine that understands document layout and visual context for retrieval.
you: not recommended
AI recommended (in order):
1. LayoutLMv3 (microsoft/unilm)
2. Donut (naver-ai/donut)
3. DocILE
4. OpenSearch (opensearch-project/OpenSearch)
5. Weaviate (weaviate/weaviate)
6. Milvus (milvus-io/milvus)
AI recommended 6 alternatives but never named StarTrail-org/PixelRAG. 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 StarTrail-org/PixelRAG?
pass
AI named StarTrail-org/PixelRAG explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts StarTrail-org/PixelRAG in production, what risks or prerequisites should they evaluate first?
pass
AI named StarTrail-org/PixelRAG 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 StarTrail-org/PixelRAG solve, and who is the primary audience?
pass
AI named StarTrail-org/PixelRAG explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/StarTrail-org/PixelRAG.svg)](https://repogeo.com/en/r/StarTrail-org/PixelRAG)

HTML

<a href="https://repogeo.com/en/r/StarTrail-org/PixelRAG"><img src="https://repogeo.com/badge/StarTrail-org/PixelRAG.svg" alt="RepoGEO" /></a>

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StarTrail-org/PixelRAG — 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