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
Yolov5 is the strongest overall pick here because it has a 100/100 readiness score and fits Coding agents.
Strongest overall
Yolov5
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Yolov5
Best first install candidate based on install readiness and adoption.
Freshest repo
OnnxStream
Most recent maintenance signal among this shortlist.
| Signal | OnnxStream Lightweight inference library for ONNX files, written in C++. It can run Stable Diffusion XL 1.0 on a RPI Zero 2 (or in 298MB of RAM) but also Mistral 7B on desktops and servers. ARM, x86, WASM, RISC-V supported. Accelerated by XNNPACK. Python, C# and JS(WASM) bindings available. | Onnxruntime ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator | Yolov5 Ultralytics YOLOv5 in PyTorch > ONNX > CoreML > TFLite | 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 |
|---|---|---|---|---|
| Quality | 100/100 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 | 2.1K stars 0 installs | 21K stars 0 installs | 58K stars 0 installs | 18K stars 0 installs |
| Freshness | Jun 18, 2026 | Jun 16, 2026 | Jun 12, 2026 | May 19, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | C++, Machine Learning, Claude Code | C++, Machine Learning, Claude Code | Python, Machine Learning, Claude Code | Jupyter Notebook, Machine Learning, Claude Code, LangChain |
| Warnings | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| Best for | Workflow automation workflows · Claude Code teams · teams that value GitHub adoption signals | GitHub automation 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 |
| 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 | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add vitoplantamura/OnnxStream | $ npx skills add microsoft/onnxruntime | $ npx skills add ultralytics/yolov5 | $ npx skills add meta-llama/llama-cookbook |