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jetty

Automate Jetty workflow orchestration and asset management via CLI and API.

3|2|Updated Feb 6, 2026
Search Tags:#automation#workflow#templates#api#cli#runbooks#jetty
One-click install
npx skills add https://github.com/jettyio/jettyio-skills --skill jetty
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: jetty
Source: https://github.com/jettyio/jettyio-skills/tree/main/skills/jetty
Command: npx skills add https://github.com/jettyio/jettyio-skills --skill jetty

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Jetty Workflow Management Skill centralizes and automates the creation, execution, deployment, and monitoring of AI/ML workflows in Jetty, reducing manual setup and operational friction across collections, tasks, and trajectories.

Core Features & Use Cases

  • End-to-end workflow orchestration: create, run, monitor, and manage collections, tasks, datasets, models, and trajectories.
  • Template-driven templates and runbooks: leverage ready-to-run workflow templates and runbooks to accelerate automation, testing, and deployment.
  • Secure, auditable operations: manage tokens, environment variables, secrets, and preflight checks to ensure safe and compliant runs.

Quick Start

Install the Jetty skill and run /jetty-setup to configure your API token, then use the /jetty CLI to manage workflows.

Frequently Asked Questions about jetty

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate AI workflow orchestration for tasks and datasets from the command line?▼

You can automate AI workflow orchestration by using the Jetty CLI to create, run, and monitor collections, tasks, datasets, and models. It centralizes deployment and reduces manual operational friction across your ML pipelines.

What do I need to configure before running Jetty workflow templates and runbooks?▼

Before running Jetty workflow templates and runbooks, you must configure a Jetty API token in the ~/.config/jetty/token file. You can set this up quickly by running the /jetty-setup command to enable secure CLI access.

Can I manage environment variables and secrets when deploying ML models?▼

Yes, you can manage environment variables and secrets when deploying ML models. The Jetty CLI supports environment-variable management and preflight checks to ensure your workflow runs and deployments remain secure and auditable.

What is the best way to monitor running trajectories and debug AI workflows?▼

The best way to monitor running trajectories and debug AI workflows is through the Jetty CLI. It provides built-in commands to track execution status, inspect task trajectories, and debug issues across your automated collections.

Does this workflow automation approach support template-driven runbooks for deployment?▼

Yes, this workflow automation approach supports template-driven runbooks. You can leverage ready-to-run templates and runbooks through run configurations to accelerate the testing, deployment, and execution of your AI workflows.

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