Queue long-running tasks with pueue and stream completion notifications.
npx skills add https://github.com/archibate/archibate-skills --skill pueue
Please help me install this Agent Skill. Skill: pueue Source: https://github.com/archibate/archibate-skills/tree/main/skills/pueue Command: npx skills add https://github.com/archibate/archibate-skills --skill pueue
The skill helps users orchestrate long-running, non-interactive tasks by queuing them with pueue and streaming completion notifications.
Start a long-running task in the background by running the wrapper script with your command, e.g., Bash("scripts/run_in_pueue.sh 'uv run python -u train.py'", run_in_background: true).
High-intent search queries and answers about installing and using this skill.
Queue long-running bash scripts with pueue to execute them in the background and stream completion notifications automatically. This avoids manual polling by using a wrapper script to add and monitor tasks safely.
Yes, you can run parallel batch jobs with dependencies using pueue. It orchestrates compute-heavy workflows and data preprocessing pipelines by supporting per-project groups and enforcing safe concurrency limits for background execution.
The best way to queue non-interactive tasks for parallel execution is using pueue. It provides a daemon to orchestrate compute-heavy workflows, automatically following task progress and sending notifications upon completion.
Yes, you need pueue, pueued, and jq installed to use this background task orchestration. The skill enforces usage of the pueue CLI and daemon to queue tasks and stream completion notifications.
Start a background job pipeline by running the wrapper script with your command, for example Bash("scripts/run_in_pueue.sh 'uv run python -u train.py'", run_in_background: true). This queues the task with pueue and monitors it automatically.
You should not use pueue for interactive tasks or workflows that require real-time user input. It is designed specifically for long-running, non-interactive background jobs, experiments, and compute-heavy pipelines with dependencies.
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