From bopen-tools
Finds stale and resource-hungry processes, scores waste, and presents cleanup report. Activates on RAM queries or slow machine, or proactively when noticing sluggishness.
How this skill is triggered — by the user, by Claude, or both
Slash command
/bopen-tools:process-cleanupThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Autonomously investigate running processes, score them by waste (resources x staleness), and produce a categorized report with friendly names and ready-to-use kill commands.
Autonomously investigate running processes, score them by waste (resources x staleness), and produce a categorized report with friendly names and ready-to-use kill commands.
This skill runs without user interaction. Gather everything, analyze, score, and present the full report. The user decides what to kill after reading it.
Run the bundled script — it handles all data collection, scoring, and safety classification in one pass:
bash ${CLAUDE_PLUGIN_ROOT}/skills/process-cleanup/scripts/cleanup-report.sh
The script outputs structured JSON to stdout (progress messages go to stderr). Parse the JSON to build your report.
ps -eo pid,ppid,rss,%cpu,lstart,tty,command)lsof -iTCP -sTCP:LISTEN)lsof -c node -c bun -c next -c python -c ruby -a -d cwd){
"my_pid": 12345,
"total_recoverable_mb": 4300,
"safe": [{"pid": 38585, "name": "Claude Code (resumed session, likely stale)", "memory_mb": 4300, "age_hours": 456, "score": 92, "port": null}],
"caution": [{"pid": 28755, "name": "Next.js dev -> agentcraft", "memory_mb": 156, "age_hours": 48, "score": 45, "port": "3000"}],
"protected": [{"pid": 76187, "name": "Claude Code -> prompts", "memory_mb": 553, "age_hours": 1, "score": 21, "port": null}],
"kill_command": "kill 38585 ..."
}
The score field is already computed (0-100, resources + staleness + replaceability). Use it directly for sorting.
The script applies these mappings automatically. This table is for your reference when the script output looks unexpected:
| Pattern in command | Friendly name |
|---|---|
claude (bare or -c) | Claude Code -> {project} |
claude --resume | Claude Code (resumed session, likely stale) |
claude.*--claude-in-chrome | Claude Chrome bridge |
opencode | OpenCode session |
codex | Codex app |
next dev or next-router-worker | Next.js dev -> {project} |
bun dev | Bun dev -> {project} |
vite | Vite dev -> {project} |
convex dev | Convex dev -> {project} |
portless | Portless proxy -> {project} |
turso | Turso DB |
postgres | PostgreSQL |
redis-server | Redis |
mongod | MongoDB |
node.*webpack|esbuild|turbopack | Bundler watcher |
tsc.*--watch | TypeScript watcher |
Google Chrome Helper | Chrome (renderer) |
Dia.*Helper | Dia browser (renderer) |
Wispr Flow | Wispr Flow voice |
iTerm2 | iTerm terminal |
Electron|Helper (Renderer) | Derive app name from path |
Present findings as a single report. Sort by waste score descending within each safety tier.
## Process Cleanup Report
**Total recoverable**: ~X.X GB across N processes
### SAFE TO KILL (X.X GB)
| Score | Process | Memory | Age | PID |
|-------|--------------------------------|---------|----------|-------|
| 92 | Claude Code (Feb 14, stale) | 4.3 GB | 19 days | 38585 |
| 78 | OpenCode (x15 sessions) | 1.3 GB | 25-31 d | ... |
### USE CAUTION (X.X GB)
| Score | Process | Memory | Age | PID |
|-------|--------------------------------|---------|----------|-------|
| 45 | Next.js dev → agentcraft | 156 MB | 2 days | 28755 |
### PROTECTED
- This Claude session — 553 MB — PID 76187
- Chrome (47 tabs) — 2.9 GB
- iTerm2 — 264 MB
Rules for the report:
End with kill commands:
# SAFE — reclaim ~X.X GB
kill PID1 PID2 PID3
# CAUTION — review first:
# kill PID4 # Next.js dev → agentcraft :3000 (156 MB)
Then state what you recommend and let the user decide.
npx claudepluginhub b-open-io/claude-plugins --plugin bopen-toolsCalculates SCUM scores for processes based on CPU, memory, and runtime to identify resource hogs. Provides bash/awk commands, babashka script, and justfile recipes to view, classify, and kill them. Useful for high system load debugging.
Monitors CPU, memory, disk, and network resources using bash commands and Node.js scripts. Analyzes usage patterns, detects issues like leaks/bottlenecks, sets alerts, and recommends optimizations.
Tracks CPU, memory, disk I/O, and network usage with top, ps, vmstat, iostat to identify bottlenecks and optimize resource allocation/costs.