agentinel

name

agentinel

description

Inspect this machine's live resource usage via the Agentinel CLI — find runaway / zombie / leaking AI-agent processes (Claude Code, Codex, Gemini, OpenCode, MCP & dev servers, Ollama…), duplicate sessions, heavy memory users, and reclaimable disk caches. Use when the user asks what's eating RAM/CPU/disk, whether they have forgotten or leaking agent sessions, which agents are still running, or wants a cleanup recommendation. Read-only — it never kills or deletes.

Agentinel — local resource sentinel (CLI)

Agentinel ships a zero-overhead CLI (~12 MB, no WebView) that snapshots every process on the machine, classifies AI-agent CLIs, and flags leaks / zombies / duplicate sessions / heavy disk. Use it to answer "what's going on with my machine right now" without guessing.

When to use

Trigger when the user asks things like:

• "What's eating my RAM / CPU?" · "為什麼這麼吃記憶體?" · "什么最吃内存?"
• "Do I have any zombie or forgotten agent sessions?" · "有沒有忘了關的 agent?"
• "Which Claude / Codex sessions are still running?"
• "Is anything leaking?" · "What can I clean up on disk?" · "磁碟可以清什麼?"

How to run

Run from the repo root (or anywhere agent_monitor/ is importable). The wrapper ./agentinel auto-finds a sibling .venv; otherwise use python -m agent_monitor. Prefer --json for parsing, fall back to the text table for display.

agentinel scan --json                 # whole-system snapshot (parse this)
agentinel scan --agents-only --json   # AI agents only
agentinel scan --top 50               # text table, top 50
agentinel advise                      # local AI CLI writes markdown advice
agentinel advise --engine codex       # pick the engine (claude|codex|gemini|opencode)
agentinel doctor                      # which AI CLIs are installed + fallback order
# (equivalently:  python -m agent_monitor <subcommand> …)

What scan --json returns

{ system, processes[], findings[] }:

• system: ram_used_gb, ram_total_gb, ram_pct, cpu_pct, swap_used_gb, swap_total_gb
• processes[]: pid, label, category, project, mem_mb, cpu, age_hr, idle_min, parent_name, parent_alive, ports[], children, cmdline
• findings[]: rule-engine anomalies — { severity, title, detail, pids, action }

How to respond

1. Summarize the 1–2 things that matter most (biggest RAM users, suspected leaks, idle zombies, duplicate sessions in the same project).
2. Cite concrete evidence: memory size/growth, idle_min, parent_alive=false, bound ports, child count.
3. Recommend keep / end / watch for each — but do not kill or delete anything.

Safety

• scan / advise / doctor are read-only. There is no CLI kill or cleanup — do not invent one. Destructive actions (kill / suspend / disk cleanup) live only in the GUI's confirm-to-run flow (python agentinel.py). If the user wants to act, point them there, or ask for explicit confirmation before running anything destructive.