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.

Add more skills

Decision summary

Langfuse is the strongest overall pick here because it has a 100/100 readiness score and fits Coding agents.

Strongest overall

Langfuse

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Fastest prototype

Langfuse

Best first install candidate based on install readiness and adoption.

Freshest repo

Langfuse

Most recent maintenance signal among this shortlist.

SignalVllm Ascend

Community maintained hardware plugin for vLLM on Ascend

BentoML

The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!

Langfuse

🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

Opik

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

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.

Adoption2.2K stars
0 installs
8.7K stars
0 installs
29K stars
0 installs
20K stars
0 installs
FreshnessJun 12, 2026Jun 3, 2026Jun 12, 2026Jun 12, 2026
Use-case fit
Stack fit
Platform hintsC++, LLMOps, Claude CodePython, LLMOps, Claude CodeTypeScript, LLMOps, Claude Code, OpenAI Agents, LangChainPython, LLMOps, Claude Code, LangChain
WarningsNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yetNo major risk signals from current metadata
Best forCoding agents workflows · Claude Code teams · teams that value GitHub adoption signalsBrowser automation workflows · Claude Code teams · teams that value GitHub adoption signalsCoding agents workflows · Claude Code teams · teams that value GitHub adoption signalsCoding agents workflows · Claude Code teams · teams that value GitHub adoption signals
Not ideal forteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security review
OpenAgentSkill engagement0 views
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Install
$ npx skills add vllm-project/vllm-ascend
$ npx skills add bentoml/BentoML
$ npx skills add langfuse/langfuse
$ npx skills add comet-ml/opik