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
Handson Ml is the strongest overall pick here because it has a 100/100 readiness score and fits Coding agents.
Strongest overall
Handson Ml
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Handson Ml
Best first install candidate based on install readiness and adoption.
Freshest repo
SwanLab
Most recent maintenance signal among this shortlist.
| Signal | Higgsfield Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters | Llama Cookbook Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services | Handson Ml ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead. | SwanLab ⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc. |
|---|---|---|---|---|
| Quality | 76/100 Strong | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 78/100 Strong shortlist Shortlist this skill and compare it with close alternatives before production adoption. | 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 | 3.8K stars 0 installs | 18K stars 0 installs | 26K stars 0 installs | 4.0K stars 0 installs |
| Freshness | May 25, 2024 | May 19, 2026 | May 19, 2026 | Jun 16, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | Jupyter Notebook, Machine Learning, Claude Code | Jupyter Notebook, Machine Learning, Claude Code, LangChain | Jupyter Notebook, 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 OpenAgentSkill engagement data yet |
| Best for | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | Sports analytics 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 | 0 views 0 install copies |
| Install | $ npx skills add higgsfield-ai/higgsfield | $ npx skills add meta-llama/llama-cookbook | $ npx skills add ageron/handson-ml | $ npx skills add SwanHubX/SwanLab |