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 teachgit 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/teach)<a href="https://agentmods.dev/skills/danielmiessler/lifeos/teach"><img src="https://agentmods.dev/badge/skills/danielmiessler/lifeos/teach/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/teach"><img src="https://agentmods.dev/badge/skills/danielmiessler/lifeos/teach.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 17 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00126 | $0.00829 |
| Opus 5.5 | $0.00050 | $0.00332 |
| Sonnet 5.5 | $0.00025 | $0.00166 |
| Haiku 4.5 | $0.00013 | $0.00083 |
Grade A, and why
Teach scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST http://localhost:31337/notify \ How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Teach
Turns the current conversation topic into a live, spoken, Socratic tutorial. Each teaching beat is narrated aloud through the voice system, drawn as ASCII in the terminal, and ends with one question to the learner. The session is a dialogue: answer, response, next beat, quiz, recap.
Voice Notification
When executing a workflow, do BOTH:
-
Send voice notification:
curl -s -X POST http://localhost:31337/notify \ -H "Content-Type: application/json" \ -d '{"message": "Starting a tutorial on TOPIC"}' \ > /dev/null 2>&1 & -
Output text notification:
Running the **Teach** workflow in the **Teach** skill to tutor TOPIC...
Workflow Routing
| Workflow | Trigger | File |
|---|---|---|
| Teach | "teach me", "/teach-me", "tutorial", "quiz me" | Workflows/Teach.md |
Gotchas
- The completion hook already speaks the
🗣️closer line. Never repeat the beat's narration in the closer or the learner hears it twice. The intended shape: the narration curl speaks the teaching, the closer carries the question — two distinct voice moments per turn. - Spoken text goes to TTS raw. No markdown, no ASCII art, no code, no symbols in the curl
message— they get read aloud literally. Write narration as plain spoken English and spell out anything a voice would say differently ("H T T P" reads better than "HTTP" for some engines; when unsure, rephrase). - One narration curl per turn, ≲350 characters. Multiple rapid POSTs queue and overlap into noise, and long messages become a synthesized wall. If a beat needs more speech than that, the beat is too big — split it.
- A beat ends at its question. Stop the turn there. Answering your own question and continuing turns the tutorial back into a lecture — the failure mode this skill exists to prevent.
- Voice endpoint down (non-200 or connection refused): keep teaching, silently text-only. Note it once at session start; do not retry every beat.
What ships with it
1 file 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.
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.
- 1mo ago First seen · 66 lines · 126 tokens per session scan A 1589523cce1d
Teach is a skill published in the GitHub repository danielmiessler/LifeOS (19,501 stars, last pushed 1mo ago), licensed MIT. It adds 126 tokens to every session and 829 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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