Skill comparison
Compare agent skills before installing.
Comparing 4 skills
Use this as a shortlist, then open the skill detail page before adopting.
Decision summary
Tesseract is the strongest overall pick here because it has a 100/100 readiness score and fits Document processing.
Strongest overall
Tesseract
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Tesseract
Best first install candidate based on install readiness and adoption.
Freshest repo
Bisheng
Most recent maintenance signal among this shortlist.
| Signal | AI Hands On A group of notebooks and other files which can help you learn AI from scratch. | Bisheng BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more. | Tesseract Tesseract Open Source OCR Engine (main repository) | X AnyLabeling Effortless data labeling with AI support from Segment Anything and other awesome models. |
|---|---|---|---|---|
| Quality | 96/100 Excellent | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 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. | 100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack. |
| Adoption | 1.1K stars Verified outcomes are shown on each skill page | 11K stars Verified outcomes are shown on each skill page | 75K stars Verified outcomes are shown on each skill page | 9.5K stars Verified outcomes are shown on each skill page |
| Freshness | Jun 2, 2026 | Jun 29, 2026 | Jun 13, 2026 | Jun 20, 2026 |
| Use-case fit | ||||
| Workflow fit | ||||
| Platform hints | Jupyter Notebook, OCR, Claude Code | TypeScript, OCR, Claude Code, OpenAI Agents | C++, OCR, Claude Code | Python, OCR, Claude Code |
| Warnings | No major risk signals from current metadata | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| 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 | Document processing 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 | 3 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add Ramakm/ai-hands-on | $ npx skills add dataelement/bisheng | $ npx skills add tesseract-ocr/tesseract | $ npx skills add CVHub520/X-AnyLabeling |