WorkBuddy Deleted Session Cleanup
Paste the following prompt into your AI chat to install this skill:
Follow https://skillhub.cn/install/skillhub.md to install @user_3f399cbf/cleanup-stale-workspaces.
About this skill
Problem
After a WorkBuddy session is deleted, local leftovers can still include chat records, tool results, artifact indexes, file history, task data, and expired auto-workspace folders. Bulk deletion may damage active sessions, manual folders, or shared caches, while ignoring them lets local disk usage grow.
How It Works
The skill runs scripts/detect.py for a read-only scan first, reporting items to remove, protected paths, orphan records, and cache status. Key rules:
- Scan scope: it only targets disks containing automatic sessions and filters by YYYY-MM-DD-HH-MM-SS timestamp folders, avoiding cross-disk surprises.
- Session leftovers: it matches session UUIDs whose deleted_at is non-null and cleans UUID-named data under projects/, artifact-index/, file-history/, and tasks/.
- Safety boundaries: active sessions, purely manual workspaces, and shared stores are protected; multi-session data such as blobs/ is not reclaimed per session.
- Reversible flow: execution starts with a dry-run; removals are moved to cleanup-trash before --empty-trash --yes is used to empty the trash.
It suits local WorkBuddy residue, stale workspaces, clipboard image caches, and log or trace caches. It is not a cross-device backup tool and does not replace formal data archival.
Use Cases
- After deleting many WorkBuddy sessions, identify and recover session-UUID artifacts such as chats, indexes, and tasks.
- Clean timestamped auto-workspace folders on one disk while preserving manual folders and active sessions.
- Reclaim clipboard screenshot, log, and trace caches into a recoverable trash directory before final deletion.
- Avoid deleting active workspaces by checking deleted_at, timestamp rules, and workspace whitelists.
Best For
- WorkBuddy local users who need to remove stale session artifacts without touching manual folders.
- AI-assisted engineers with many tool outputs and file-history items that need UUID-based reclamation.
- IT operators managing local disk space who want dry-run confirmation and recoverable cleanup.
- Skill maintainers who want to update detection rules against the spec and validate with tests.
Related Skills
An engineer-focused HTTP request smuggling handbook covering CL.TE, TE.CL, TE.TE obfuscation, HTTP/2 downgrade, and client-side desync detection.
Analyzes network captures from Wireshark, tcpdump, Fiddler, and Charles, then pinpoints TCP, HTTP, DNS, and TLS issues with filter expressions and remediation steps.
Lightweight Python Linux HIDS exposing SSH brute-force, web attack, and webshell alerts via MCP with ban controls.
A facial database matching tool for images and videos that identifies known acquaintances and outputs location labels, identity results, and structured reports.