Windows Top 10 Largest File Scanner
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About this skill
Problem to solve
On Windows systems, disk usage issues often come down to locating a few unexpectedly large files. Manually browsing C:/Users, project folders, or log directories is slow, especially when large files may be nested several levels deep or spread across many subdirectories.
How the skill works
The skill runs a PowerShell scan pipeline with a small set of controls:
- Scope the scan: pass a directory with
-path; the script resolves the path and exits if the location is missing or inaccessible. - Collect files only:
Get-ChildItem -Filegathers files, while-depthcan limit recursion;-1scans without a depth cap. - Rank results: files are sorted by size in descending order and truncated to the top 10, with total file count, total size, and duration also reported.
- Readable output: a colored table shows rank, byte size, human-readable size, relative path, and a proportional bar.
- Machine-readable output: a JSON block between
---JSON_OUTPUT_START---and---JSON_OUTPUT_END---exposestop10, paths, sizes, modification times, and scan statistics.
Boundaries to keep in mind
This is useful for quick Windows file-level triage, not a full disk audit or permission review. Unlimited depth can be slow on large trees, inaccessible files are skipped, and results rank individual files rather than aggregate folder size. For automation, parse the JSON section instead of the colored table.
Use Cases
- Windows operators scan C:/Users with -path to find the top 10 largest files when user profiles look full.
- IT support limits D:/Projects scans with -depth 2 to locate oversized logs or exported files before cleanup.
- Automation engineers parse the JSON_OUTPUT block to read top10 and total_size_bytes in OpenClaw flows.
- Developers use -unit GB to inspect the largest package files under D:/build during build-artifact triage.
Best For
- Windows operators handling disk alerts by locating the largest files first.
- IT support agents checking user profiles before cleanup to identify big files.
- Automation engineers feeding the JSON top10 results into OpenClaw workflows.
- Developers reviewing project folders for large build artifacts or logs.
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