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 | BerryNet Deep learning gateway on Raspberry Pi and other edge devices | Tasmota Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at | 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 | 72/100 Strong | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 74/100 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 | 1.6K stars 0 installs | 24K stars 0 installs | 162K stars 0 installs | 43K stars 0 installs |
| Freshness | Feb 16, 2023 | Jun 16, 2026 | Jun 16, 2026 | Jun 16, 2026 |
| Use-case fit | ||||
| Workflow fit | ||||
| Platform hints | Python, IoT, Claude Code | C, Automation, 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 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 | 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 | 0 views 0 install copies |
| Install | $ npx skills add DT42/BerryNet | $ npx skills add arendst/Tasmota | $ npx skills add huggingface/transformers | $ npx skills add ray-project/ray |