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.
Decision summary
MinerU is the strongest overall pick here because it has a 100/100 readiness score and fits Document processing.
Strongest overall
MinerU
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
MinerU
Best first install candidate based on install readiness and adoption.
Freshest repo
MinerU
Most recent maintenance signal among this shortlist.
| Signal | Dedoc 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. | OpenOCR OpenOCR: An Open-Source Toolkit for General-OCR Research and Applications, integrates a unified training and evaluation benchmark, commercial-grade OCR and Document Parsing systems, and faithful reproductions of the core implementations from a wide range of academic papers. | Docext An on-premises, OCR-free unstructured data extraction, markdown conversion and benchmarking toolkit. (https://idp-leaderboard.org/) |
|---|---|---|---|---|
| Quality | 80/100 Strong | 100/100 Excellent | 100/100 Excellent | 98/100 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. |
| Adoption | 712 stars 0 installs | 68K stars 0 installs | 1.4K stars 0 installs | 2.0K stars 0 installs |
| Freshness | May 4, 2026 | Jun 15, 2026 | May 20, 2026 | Mar 17, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | Python, OCR, Claude Code | Python, PDF, Claude Code | Python, OCR, Claude Code | Python, OCR, Claude Code |
| Warnings | No major risk signals from current metadata | No OpenAgentSkill engagement data yet | No major risk signals from current metadata | No major risk signals from current metadata |
| Best for | Document processing workflows · Claude Code teams · teams that value GitHub adoption signals | Document processing workflows · Claude Code teams · teams that value GitHub adoption signals | Research agents workflows · Claude Code teams · teams that value GitHub adoption signals | Document processing workflows · Claude Code teams · teams that value GitHub adoption signals |
| Not ideal for | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review |
| OpenAgentSkill engagement | 1 views 0 install copies | 0 views 0 install copies | 3 views 0 install copies | 1 views 0 install copies |
| Install | $ npx skills add ispras/dedoc | $ npx skills add opendatalab/MinerU | $ npx skills add Topdu/OpenOCR | $ npx skills add NanoNets/docext |