Identify and remediate directory structure violations with approval-gated cleanup workflows.
npx skills add https://github.com/EndUser123/cc-skills-utils --skill cleanup-enduser123
Please help me install this Agent Skill. Skill: cleanup Source: https://github.com/EndUser123/cc-skills-utils/tree/main/skills/cleanup Command: npx skills add https://github.com/EndUser123/cc-skills-utils --skill cleanup-enduser123
Review and remediate directory structure violations using an interactive cleanup handler with approval gates.
Run the cleanup workflow in dry-run mode to identify directory violations and then apply approved fixes.
High-intent search queries and answers about installing and using this skill.
You can remediate directory structure violations using an LLM-guided cleanup workflow that performs source-code analysis and requires explicit approvals before applying destructive fixes.
The best way to automate directory cleanup safely is using a dry-run mode that identifies violations first, followed by an interactive cleanup phase with reference checks before any deletion occurs.
An LLM-guided cleanup workflow identifies directory policy violations by analyzing your source code structure in a first phase, then guiding interactive remediation in a second phase.
Yes, you can run directory cleanup in auto-approve mode, but the workflow enforces safety constraints with explicit approval gates and reference checks before executing destructive actions.
Automated directory remediation scripts require explicit approvals for destructive actions and perform reference checks before deletion, meaning full auto-remediation is constrained by safety gates.
You need an environment that supports script execution for policy-driven checks, as the workflow relies on scripts to analyze directory structures and enforce safety constraints during remediation.
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