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
Transformers is the strongest overall pick here because it has a 100/100 readiness score and fits Multimodal media.
Strongest overall
Transformers
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Transformers
Best first install candidate based on install readiness and adoption.
Freshest repo
Transformers
Most recent maintenance signal among this shortlist.
| Signal | Sars Tutorial Repository for the tutorial on Sequence-Aware Recommender Systems held at TheWebConf 2019 and ACM RecSys 2018 | Handson Ml ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead. | Transformers 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. | Ray Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads. |
|---|---|---|---|---|
| Quality | 52/100 Needs review | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 42/100 Needs manual review Do a manual repository review before adding this to an agent workflow. | 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 | 344 stars Verified outcomes are shown on each skill page | 26K stars Verified outcomes are shown on each skill page | 162K stars Verified outcomes are shown on each skill page | 43K stars Verified outcomes are shown on each skill page |
| Freshness | Jan 27, 2021 | May 19, 2026 | Jun 16, 2026 | Jun 16, 2026 |
| Use-case fit | ||||
| Workflow fit | ||||
| Platform hints | Python, Machine Learning, Claude Code | Jupyter Notebook, Machine Learning, Claude Code | Python, Machine Learning, Claude Code | Python, Machine Learning, Claude Code |
| Warnings | Repository looks stale · No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No major risk signals from current metadata |
| Best for | Coding agents workflows · Claude Code teams · builders willing to evaluate younger projects | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | Multimodal media workflows · Claude Code teams · teams that value GitHub adoption signals | RAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signals |
| Not ideal for | teams that require actively maintained dependencies · production agents without a repository 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 | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies | 35 views 1 install copies |
| Install | $ npx skills add mquad/sars_tutorial | $ npx skills add ageron/handson-ml | $ npx skills add huggingface/transformers | $ npx skills add ray-project/ray |