Skill comparison

Compare agent skills before installing.

Put high-signal skills side by side and inspect quality, adoption, freshness, install readiness, use-case fit, and warnings in one place.

Comparing 4 skills

Use this as a shortlist, then open the skill detail page before adopting.

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Decision summary

PaddleOCR is the strongest overall pick here because it has a 100/100 readiness score and fits Document processing.

Strongest overall

PaddleOCR

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Fastest prototype

PaddleOCR

Best first install candidate based on install readiness and adoption.

Freshest repo

Docling

Most recent maintenance signal among this shortlist.

SignalDedoc

Dedoc is a library (service) for automate documents parsing and bringing to a uniform format. It automatically extracts content, logical structure, tables, and meta information from textual electronic documents. (Parse document; Document content extraction; Logical structure extraction; PDF parser; Scanned document parser; DOCX parser; HTML parser

MinerU

Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.

Docling

Get your documents ready for gen AI

PaddleOCR

Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.

Quality
80/100
Strong
100/100
Excellent
100/100
Excellent
100/100
Excellent
Decision verdict
91/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

100/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

100/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

100/100
Production-ready

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Adoption712 stars
Verified outcomes are shown on each skill page
68K stars
Verified outcomes are shown on each skill page
63K stars
Verified outcomes are shown on each skill page
83K stars
Verified outcomes are shown on each skill page
FreshnessJun 24, 2026Jun 17, 2026Jul 17, 2026Jun 16, 2026
Use-case fit
Workflow fit
Platform hintsPython, OCR, Claude CodePython, PDF, Claude CodePython, PDF, Claude CodePython, OCR, Claude Code
WarningsNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yet
Best forDocument processing workflows · Claude Code teams · teams that value GitHub adoption signalsDocument processing workflows · Claude Code teams · teams that value GitHub adoption signalsDocument processing workflows · Claude Code teams · teams that value GitHub adoption signalsDocument processing workflows · Claude Code teams · teams that value GitHub adoption signals
Not ideal forteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security review
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Install
$ npx skills add ispras/dedoc
$ npx skills add opendatalab/MinerU
$ npx skills add docling-project/docling
$ npx skills add PaddlePaddle/PaddleOCR