REPOGEO REPORT · LITE

wisupai/e2m

Default branch main · commit ff89c7ae · scanned 6/30/2026, 2:43:28 PM

GitHub: 1,295 stars · 73 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 wisupai/e2m, 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's first paragraph to emphasize RAG/LLM data preparation

Why:

CURRENT

E2M is a Python library that can parse and convert various file types into Markdown format. By utilizing a parser-converter architecture, it supports the conversion of multiple file formats, including doc, docx, epub, html, htm, url, pdf, ppt, pptx, mp3, and m4a.

COPY-PASTE FIX

E2M is a Python library designed to parse and convert diverse file types (including doc, docx, epub, html, url, pdf, ppt, pptx, mp3, and m4a) into high-quality Markdown format, specifically optimized for Retrieval-Augmented Generation (RAG) and LLM training data preparation.

hightopics#2

Expand repository topics to improve categorization for document conversion and LLM use cases

Why:

CURRENT

doc2x, e2m, llm, markdown, pdf-to-markdown, text-cleaning

COPY-PASTE FIX

doc2x, e2m, llm, markdown, pdf-to-markdown, text-cleaning, rag, llm-data-preparation, document-conversion, file-converter, python-library, docx-to-markdown, pptx-to-markdown, html-to-markdown, epub-to-markdown

mediumhomepage#3
Add the repository URL as the homepage
Why:
COPY-PASTE FIX
```
https://github.com/wisupai/e2m
```

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 wisupai/e2m

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Unstructured-IO/unstructured

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Unstructured-IO/unstructured · recommended 1×
jgm/pandoc · recommended 1×
apache/tika · recommended 1×
mwilliamson/mammoth.js · recommended 1×
mwilliamson/python-mammoth · recommended 1×

CATEGORY QUERY
How can I convert diverse document types like PDFs and Word files into Markdown for LLM training?
you: not recommended
AI recommended (in order):
1. Unstructured.io (Unstructured-IO/unstructured)
2. Pandoc (jgm/pandoc)
3. Apache Tika (apache/tika)
4. mammoth.js (mwilliamson/mammoth.js)
5. python-mammoth (mwilliamson/python-mammoth)
6. pdfminer.six (pdfminer/pdfminer.six)
7. Microsoft Graph API
8. html2text (Alir3z4/html2text)
9. Google Docs API
10. Tesseract (tesseract-ocr/tesseract)
11. Google Cloud Vision
12. AWS Textract
13. Azure AI Vision
AI recommended 13 alternatives but never named wisupai/e2m. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a Python library to programmatically convert many file formats into clean Markdown text.
you: not recommended
AI recommended (in order):
1. pypandoc
2. unstructured
3. python-mammoth
4. markdownify
5. textract
6. pdfminer.six
7. docx2txt
AI recommended 7 alternatives but never named wisupai/e2m. 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 wisupai/e2m?
pass
AI named wisupai/e2m explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts wisupai/e2m in production, what risks or prerequisites should they evaluate first?
pass
AI named wisupai/e2m 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 wisupai/e2m solve, and who is the primary audience?
pass
AI named wisupai/e2m 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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Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/wisupai/e2m.svg)](https://repogeo.com/en/r/wisupai/e2m)

HTML

<a href="https://repogeo.com/en/r/wisupai/e2m"><img src="https://repogeo.com/badge/wisupai/e2m.svg" alt="RepoGEO" /></a>

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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite