set-up

Automates end-to-end setup of a new agent workflow track.

3|2|Updated Mar 20, 2026
One-click install
npx skills add https://github.com/jvdheyden/jobwatch --skill set-up
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: set-up
Source: https://github.com/jvdheyden/jobwatch/tree/main/.agents/skills/set-up
Command: npx skills add https://github.com/jvdheyden/jobwatch --skill set-up

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the creation and provisioning of a new track for the job-agent workflow, transforming a setup idea into a concrete, runnable scaffold with the necessary configuration.

Core Features & Use Cases

  • Automates local profile and prefs preparation, including initial global and track-specific context.
  • Generates and initializes track configuration files (prefs.md, sources.json, match_rules.json, source_state.json, AGENTS.md, CLAUDE.md, GEMINI.md) and accompanying documentation scaffolds.
  • Validates the initial digest pipeline by producing a first digest skeleton suitable for review and iteration.
  • Example use: a developer wants to bootstrap a new track to monitor a fresh set of sources with minimal manual steps and guided prompts.

Quick Start

Set up a new job-agent track by providing the track display name, slug, goals, and starter sources.

Frequently Asked Questions about set-up

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

FAQPage Schema
How do I automate job-agent track setup end-to-end from a list of starter sources?

Automating job-agent track setup is handled by generating configuration scaffolds like sources.json and match_rules.json, running initial validation commands, and producing a first-digest skeleton for local review. It coordinates profile prep, source normalization, and canary probing automatically.

What configuration files do I need to scaffold a new job-agent track?

Scaffolding a new job-agent track requires generating prefs.md, sources.json, match_rules.json, source_state.json, AGENTS.md, CLAUDE.md, and GEMINI.md. These artifacts define track preferences, source lists, matching rules, and agent-specific instructions for the workflow.

How does source normalization and canary probing work when initializing a new track?

Source normalization and canary probing work by validating starter sources during the track initialization phase. The process prepares local profiles, normalizes incoming source data, probes sources for viability, and validates the initial digest pipeline before generating the final configuration.

Can I bootstrap a new track to monitor fresh sources with minimal manual steps?

Bootstrapping a new track to monitor fresh sources with minimal manual steps is fully supported. By providing a track display name, slug, goals, and starter sources, the system adapts to existing tracks and uses guided prompts to generate all necessary configuration artifacts.

What's the best way to validate the initial digest pipeline for a new source track?

The best way to validate the initial digest pipeline is by running the built-in initial validation commands during setup. This produces a first digest skeleton locally, allowing you to review the output and iterate on match rules before full deployment.