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 usmetricsgit 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/usmetrics)<a href="https://agentmods.dev/skills/danielmiessler/lifeos/usmetrics"><img src="https://agentmods.dev/badge/skills/danielmiessler/lifeos/usmetrics/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/usmetrics"><img src="https://agentmods.dev/badge/skills/danielmiessler/lifeos/usmetrics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- 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 21 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 | $0.00120 | $0.01909 |
| Opus 5.5 | $0.00048 | $0.00764 |
| Sonnet 5.5 | $0.00024 | $0.00382 |
| Haiku 4.5 | $0.00012 | $0.00191 |
Grade A, and why
USMetrics 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customization
Before executing, check for user customizations at:
~/.claude/LIFEOS/USER/CUSTOMIZATIONS/SKILLS/USMetrics/
If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.
🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION)
You MUST send this notification BEFORE doing anything else when this skill is invoked.
-
Send voice notification:
curl -s -X POST http://localhost:31337/notify \ -H "Content-Type: application/json" \ -d '{"message": "Running the WORKFLOWNAME workflow in the USMetrics skill to ACTION"}' \ > /dev/null 2>&1 & -
Output text notification:
Running the **WorkflowName** workflow in the **USMetrics** skill to ACTION...
This is not optional. Execute this curl command immediately upon skill invocation.
US Metrics - Economic & Social Indicator Analysis
What It Does
Pulls 68 US economic and social indicators from five government APIs (FRED, EIA, Treasury, BLS, Census) across 10 categories — GDP, Inflation, Employment, Housing, Consumer Finance, Markets, Trade, Government/Fiscal, Demographics, Health — and analyzes them. Two workflows: UpdateData fetches live values into the Substrate dataset; GetCurrentState produces a multi-timeframe (10y/5y/2y/1y) trend overview with cross-metric correlation, pattern detection, and research recommendations.
The Problem
The numbers that tell you how the economy is actually doing are scattered across five federal agencies, each with its own API, its own update cadence, and its own publication lag. Pulling "how is the economy?" together by hand means hitting FRED, EIA, Treasury, BLS, and Census separately, normalizing the results, and lining up trends across different timeframes — slow, error-prone, and easy to present stale or preliminary data as if it were final. This skill collects all 68 indicators into one dataset and reads the trends across four timeframes at once.
What ships with it
5 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.
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 · 198 lines · 120 tokens per session scan A 056e61f66105
USMetrics is a skill published in the GitHub repository danielmiessler/LifeOS (19,596 stars, last pushed 1mo ago), licensed MIT. It adds 120 tokens to every session and 1,909 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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