Create and debug local-first declarative workflow jobs with Dagu
Use Dagu to define file-backed workflow jobs in YAML, run them locally or across workers, and inspect failures through a lightweight operator surface instead of a heavyweight orchestrator.
npx skills add agentskillexchange/skills --skill create-and-debug-local-first-declarative-workflow-jobs-with-dagu
Use Dagu when the job is to create, schedule, run, and repair declarative workflow jobs without standing up a large orchestration stack. The upstream project is explicit about this workflow shape: jobs are defined as DAGs in YAML, run from a single binary, scheduled with cron, and inspected through a web UI with logs, retries, and run history.
What this skill actually does
Invoke this instead of using the product normally when you need a repeatable operator loop around existing scripts, containers, data tasks, or maintenance jobs. The skill is not just “use a workflow engine”. It is specifically about authoring a file-based job, running it, checking failed steps, retrying or editing the workflow, and keeping the operational surface simple enough for local-first or air-gapped environments.
The scope boundary that keeps this skill-shaped is the concrete job lifecycle: define workflow YAML, execute it, inspect the graph and logs, and repair broken runs. That is narrower than publishing Dagu as a generic platform, server, or workflow product listing.