streaming-inference-setup
Configure streaming inference setup operations. Auto-activating skill for ML Deployment. Triggers on: streaming inference setup, streaming inference setup Part of the ML Deployment skill category. Use when working with streaming inference setup functionality. Trigger with phrases like "streaming inference setup", "streaming setup", "streaming". '
Profile →npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill streaming-inference-setup --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Streaming Inference Setup ## Overview This skill provides automated assistance for streaming inference setup tasks within the ML Deployment domain. ## When to Use This skill activates automatically when you: - Mention "streaming inference setup" in your request - Ask about streaming inference setup patterns or best practices - Need help with machine learning deployment skills covering model serv
What does the streaming-inference-setup skill do?
Configure streaming inference setup operations. Auto-activating skill for ML Deployment. Triggers on: streaming inference setup, streaming inference setup Part of the ML Deployment skill category. Use when working with streaming inference setup functionality. Trigger with phrases like "streaming inference setup", "streaming setup", "streaming". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill streaming-inference-setup --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.