REPOGEO REPORT · LITE

yobix-ai/extractous

Default branch main · commit 818d94cd · scanned 5/20/2026, 9:03:33 PM

GitHub: 1,750 stars · 95 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

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 yobix-ai/extractous, 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 clarify core function and technology

Why:

CURRENT

_Extractous offers a fast and efficient solution for extracting content and metadata from various documents types such as PDF, Word, HTML, and [many other formats](#supported-file-formats). Our goal is to deliver a fast and efficient comprehensive solution in Rust with bindings for many programming languages._

COPY-PASTE FIX

Extractous is a high-performance, local-first library for extracting content and metadata from diverse unstructured document types (PDF, Word, HTML, etc.). Built in Rust with bindings for many languages, it provides a fast, efficient alternative to external APIs and LLM-centric tools for document pre-processing and RAG pipelines.

mediumhomepage#2
Add homepage URL to repository metadata
Why:
COPY-PASTE FIX
```
https://yobix.ai
```

mediumtopics#3

Refine topics to reduce LLM-centric misinterpretation

Why:

CURRENT

data-pipelines, docx, etl, etl-pipelines, extraction, llm, machine-learning, natural-language-processing, nlp, ocr, pdf, pdf-parser, rag, rust, tika, unstructured, unstructured-data

COPY-PASTE FIX

data-pipelines, docx, etl, etl-pipelines, extraction, ocr, pdf, pdf-parser, rag, rust, tika, unstructured, unstructured-data, document-parsing, content-extraction, metadata-extraction, rust-library, python-bindings

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 yobix-ai/extractous

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

tika-rust/tika-rust

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

tika-rust/tika-rust · recommended 1×
pdf-rs/pdf-extract · recommended 1×
the-rs-toolchain/docx-rs · recommended 1×
the-rs-toolchain/xlsx-rs · recommended 1×
the-rs-toolchain/pptx-rs · recommended 1×

CATEGORY QUERY
Need a high-performance library for extracting text and metadata from various document types in Rust.
you: not recommended
AI recommended (in order):
1. Tika (tika-rust/tika-rust)
2. pdf-extract (pdf-rs/pdf-extract)
3. docx-rs (the-rs-toolchain/docx-rs)
4. xlsx-rs (the-rs-toolchain/xlsx-rs)
5. pptx-rs (the-rs-toolchain/pptx-rs)
6. calamine (tafia/calamine)
7. zip (zip-rs/zip)
8. quick-xml (tafia/quick-xml)
9. xml-rs (netvl/xml-rs)
AI recommended 9 alternatives but never named yobix-ai/extractous. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How to efficiently extract content from PDFs and Word documents for local RAG pipeline processing?
you: not recommended
AI recommended (in order):
1. Unstructured.io
2. Apache Tika
3. PyMuPDF (Fitz)
4. python-docx
5. pdfminer.six
6. Pandoc
AI recommended 6 alternatives but never named yobix-ai/extractous. 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 yobix-ai/extractous?
pass
AI named yobix-ai/extractous explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts yobix-ai/extractous in production, what risks or prerequisites should they evaluate first?
pass
AI named yobix-ai/extractous 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 yobix-ai/extractous solve, and who is the primary audience?
pass
AI named yobix-ai/extractous 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/yobix-ai/extractous"><img src="https://repogeo.com/badge/yobix-ai/extractous.svg" alt="RepoGEO" /></a>

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yobix-ai/extractous — 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