Reconcile process IDs with state files to clean stale AI agent loops.
npx skills add https://github.com/BrennonTWilliams/little-loops --skill cleanup-loops
Please help me install this Agent Skill. Skill: cleanup-loops Source: https://github.com/BrennonTWilliams/little-loops/tree/main/skills/cleanup-loops Command: npx skills add https://github.com/BrennonTWilliams/little-loops --skill cleanup-loops
This skill resolves the accumulation of orphaned, stuck, or abandoned AI agent processes that consume system resources and clutter the workspace, ensuring your development environment remains clean and efficient.
Run the cleanup-loops skill to scan your environment and interactively remove any stale or stuck loop processes.
High-intent search queries and answers about installing and using this skill.
To clean up stuck AI agent loops, you can automate the recovery process by reconciling persistent state files with active process IDs. This scans local loop directories to identify orphaned tasks and safely archives or removes them.
The best way to recover abandoned AI workflows after a crash is to audit active loops and prune stale state files. This interactively diagnoses process health, allowing you to either resume interrupted work or safely clean up abandoned tasks.
Yes, you need bash access to remove stale lock files and dead processes. Bash is required to verify active process status and manage filesystem artifacts within the local `.loops` directory structure during cleanup.
AI agent process management leaves orphaned tasks when long-running loops are interrupted by manual termination or system crashes. These interrupted processes fail to clean up their persistent state files, causing them to become stuck or stale.
Yes, you can automate the archival of interrupted agentic workflows without losing state data. The recovery workflow safely archives abandoned loop states and persistent files instead of permanently deleting them, preserving the environment while clearing clutter.
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