LifeOS is an AI-assisted personal operating system that records a person’s goals, values, context, and current situation to help move them toward a desired future state. It supports work such as building applications, starting businesses, and creative projects. Its catalogue entries extend the system through skills, hooks, agents, and commands.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add danielmiessler/LifeOS --skill computerusegit clone --depth 1 https://github.com/danielmiessler/LifeOSWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/danielmiessler/lifeos/computeruse)<a href="https://agentmods.dev/skills/danielmiessler/lifeos/computeruse"><img src="https://agentmods.dev/badge/skills/danielmiessler/lifeos/computeruse/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/danielmiessler/lifeos/computeruse"><img src="https://agentmods.dev/badge/skills/danielmiessler/lifeos/computeruse.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.03104 |
| Opus 5.5 | $0.00000 | $0.01242 |
| Sonnet 5.5 | $0.00000 | $0.00621 |
| Haiku 4.5 | $0.00000 | $0.00310 |
Grade A, and why
ComputerUse scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ComputerUse
Contents: Ideal State · Intent Routing · The routing table · The supervised run · Data & Config · Gotchas · Examples
One skill routes every computer-use task by a rule you can read, then supervises the run so the vision leg never grades itself, never sees what it must not, and never runs away.
Ideal State
- Every task is routed by the readable rule before anything runs: verification and anything with a DOM, AX, CLI or API handle go to Interceptor, and only pixel-only work goes to the measured vision pick.
- A vision run's verdict comes only from its declared verifier, never from the agent's own report, and no run starts without one.
- The vision leg never sees a running credential app, a visible communications app or a denied host, never acts outside its allowlisted app, and stops at its step and wall-clock caps.
- Send, buy, delete, publish or confirm happens only when the principal named that exact action, and every refusal is reported rather than worked around.
Intent Routing
| Intent | Trigger | File |
|---|---|---|
| Drive | "do this in the GUI", "drive ", "computer use for " | Intents/Drive.md |
| Probe | "is Astra computer use working", "probe the vision leg" | Intents/Probe.md |
| BakeOff | "bake-off", "which vision agent is better", "Claude vs OpenAI computer use", "re-score the vision legs" | Intents/BakeOff.md |
| File | Read when |
|---|---|
Instructions.md |
changing what the Astra leg is told; the runner passes it as model_instructions_file on every spawn |
Config.example.md |
setting up the deny lists, caps and Focus shortcuts in the USER Config.md |
Tests/ |
changing routing, deny rules, caps or spawn flags (fixtures under Tests/fixtures/ are synthetic; source tree only, not in the release payload) |
Setup.md |
first-time setup: the Config.md fields, the Codex app and plugin, permissions, and a dry-run proof |
References/VisionLegs.md |
changing or debugging how the Astra or Claude leg is spawned and confined: codex flags, the Claude leg step loop, its tool restrictions, env drops, pixel-to-point mapping |
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- Config.example.md 1021 B
- Instructions.md 1.0 KB
- Intents/BakeOff.md 1.7 KB
- Intents/Drive.md 2.2 KB
- Intents/Probe.md 1.3 KB
- References/VisionLegs.md 1.4 KB
- Setup.md 4.2 KB
- Tools/BakeOff.ts 11 KB runs code
- Tools/ClaudeLeg.ts 14 KB runs code
- Tools/Probe.ts 2.8 KB runs code
- Tools/Route.ts 3.9 KB runs code
- Tools/Run.ts 35 KB runs code
- Tools/WindowBounds.ts 4.1 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 110 lines · 0 tokens per session scan A 01cc07dfccd2
ComputerUse is a skill published in the GitHub repository danielmiessler/LifeOS (19,637 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,104 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-28.
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