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.
git 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/commands/danielmiessler/lifeos/context-search)<a href="https://agentmods.dev/commands/danielmiessler/lifeos/context-search"><img src="https://agentmods.dev/badge/commands/danielmiessler/lifeos/context-search/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/commands/danielmiessler/lifeos/context-search"><img src="https://agentmods.dev/badge/commands/danielmiessler/lifeos/context-search.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 | $0.00052 | $0.00114 |
| Opus 5.5 | $0.00021 | $0.00046 |
| Sonnet 5.5 | $0.00010 | $0.00023 |
| Haiku 4.5 | $0.00005 | $0.00011 |
Grade A, and why
Context Search 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 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.
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.
What it actually says
Context Search — Redirect
Thin invoker for the Cortex skill's recall workflow (sessions, ISAs, conversations by topic or date phrase).
Skill("Cortex", "recall $ARGUMENTS")
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 · 14 lines · 52 tokens per session scan A cde97f4d698d
Context Search is a command published in the GitHub repository danielmiessler/LifeOS (19,457 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 114 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
Other commands, from other repositories
setup-context
Set up your Skill Memory — a pm-context.md every skill reads so outputs come back tailored to you.
brain
Set up or use your Professional Brain — init, ingest, recall, or review.
pull-learnings
Pulls shared organization patterns into local org-patterns.toon.
perf-difficult-conversation
Three-conversations framework rehearsal (Stone/Patton/Heen — Harvard Negotiation Project) for high-stakes conversations — termination, demotion, hard feedback, conflict surfacing. Produces three-conversations breakdown (what-happened / feelings / identity), conversation script with multiple opening choices, SCARF…
culture-onboarding-90
Design a 90-day onboarding architecture for a role. First day (psychological safety + belonging activation), first week (relationship + role context + early wins), first month (skill ramp + integration + baseline), first quarter (autonomous performance + cultural integration check). Written-first elements for…
discover-genius
Excavate genius from a person's scattered corpus. Produces Genius Profile (what only they uniquely see) + Freedom Path (four-bucket sort of every activity). Gateway to all downstream intelligence systems. For humans, not agents.