cleanup

Delete outdated run records and orphaned process data beyond a retention period.

2|1|Updated May 3, 2026
One-click install
npx skills add https://github.com/a5c-ai/babysitter-omp --skill cleanup-a5c-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cleanup
Source: https://github.com/a5c-ai/babysitter-omp/tree/main/skills/cleanup
Command: npx skills add https://github.com/a5c-ai/babysitter-omp --skill cleanup-a5c-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of cleaning up old and unnecessary run data and orphaned processes, ensuring cleaner storage and improved system performance.

Core Features & Use Cases

  • Data Cleanup: Automatically identifies and deletes completed or failed run records older than a specified number of days.
  • Insight Aggregation: Summarizes historical run insights into a markdown report for review.
  • Use Case: For a DevOps team managing frequent automated runs, this Skill helps maintain disk space by removing outdated log files and orphaned process data after summarizing past activities.

Quick Start

Invoke this Skill with the --keep-days parameter to specify retention; for example, run it with default days or set a custom number to clean up old run directories.

Frequently Asked Questions about cleanup

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

FAQPage Schema
How do I automatically delete outdated run logs and orphaned process data?

You can automatically delete outdated run logs and orphaned process data by invoking a cleanup script with a specified retention parameter. This identifies completed or failed records older than a set number of days and removes them to free up storage.

What is the best way to manage storage cleanup for continuous integration logs?

Managing storage cleanup for continuous integration logs is best handled by automating the removal of temporary files and run records. This approach enforces data retention policies while maintaining system health and storage efficiency.

Can I summarize historical run insights before removing old directories?

Yes, you can summarize historical run insights before removing old directories. The process aggregates past activities into a markdown report for review, ensuring you retain relevant information before deleting the raw run data.

How do I specify a custom retention period for cleaning up task orchestration files?

You specify a custom retention period for cleaning up task orchestration files by passing a parameter like `--keep-days` with your desired number. This ensures only recent, relevant data is retained while older files are deleted.

Does this data cleanup approach work for both completed and failed automated runs?

Yes, this data cleanup approach works for both completed and failed automated runs. It identifies and deletes run records regardless of their completion status, provided they are older than your specified retention threshold.

Why does system storage fill up with orphaned files during automated workflows?

System storage fills up with orphaned files during automated workflows because continuous integration and task orchestration generate numerous temporary files and logs. Without automated cleanup, these outdated records accumulate and cause storage clutter.