starchild-ai-agent/@1892/disk-manager
1892/disk-manager/SKILL.md
Intelligent disk space management for workspace environments. Analyze storage by safety tier, run dry-run cleanup, remove safe cache artifacts, and archive old projects with dependency exclusion. Use when the user asks to free disk space, clean workspace clutter, or automate cleanup policies.
testing
Updated Apr 20, 2026
$ install --global
skillsauthnpx skillsauth add starchild-ai-agent/community-skills @1892/disk-managerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 20, 2026, 4:41 AM17.3s5 files scanned
SKILL.md
- name:
- @1892/disk-manager
- description:
- Intelligent disk space management for workspace environments. Analyze storage by safety tier, run dry-run cleanup, remove safe cache artifacts, and archive old projects with dependency exclusion. Use when the user asks to free disk space, clean workspace clutter, or automate cleanup policies.
- version:
- 1.2.0
- emoji:
- 🧹
- skillKey:
- disk-manager
- user-invocable:
- true
Disk Manager
You manage workspace disk space with an opinionated, safety-first workflow that prioritizes reclaiming space without risking user data.
What this skill is for
Use this skill when the user asks to:
- check disk usage,
- clean up storage,
- remove caches/build artifacts,
- archive inactive projects,
- or automate recurring cleanup policies.
Safety model (always follow)
Classify findings into three tiers and present results this way:
- Safe to delete — caches and bytecode (
__pycache__,.pytest_cache,.mypy_cache,.ruff_cache,*.pyc) - Recreatable — dependencies/build outputs (
node_modules,dist,build,.next,target) - Review needed — anything user-authored or potentially irreplaceable
Never delete Tier 2 or Tier 3 without explicit confirmation.
Core workflow
- Scan first
- Run
scripts/scan_workspace.pyto generate categorized opportunities.
- Run
- Show dry-run impact
- Run
scripts/safe_cleanup.py --dry-runso the user sees estimated reclaimed bytes.
- Run
- Execute approved cleanup
- For safe cleanup, run
scripts/safe_cleanup.py. - For project archival, run
scripts/archive_project.py --project <name>.
- For safe cleanup, run
- Verify after action
- Re-run scanner and report before/after reclaimed space.
Commands
1) Full workspace scan
python3 skills/disk-manager/scripts/scan_workspace.py
(Use --json for machine output)
2) Dry-run safe cleanup
python3 skills/disk-manager/scripts/safe_cleanup.py --dry-run
(Use --json for machine output)
3) Execute safe cleanup
python3 skills/disk-manager/scripts/safe_cleanup.py
(Use --json for machine output)
4) Archive inactive project
python3 skills/disk-manager/scripts/archive_project.py --project my-project
Reporting format
When reporting to the user, always include:
- total workspace bytes scanned,
- bytes reclaimable by tier,
- exact paths for top heavy items,
- estimated freed bytes (dry-run) or verified freed bytes (post-cleanup).
Keep outputs concise and actionable, and always separate recommendation from executed actions.
References
See references/cleanup-policy.md for tiering and guardrails.
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