Install LifeOS into an existing AI agent environment, then use a guided interview to capture current circumstances and goals for the Pulse dashboard. The skill also handles installation checks, updates, and removal.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Install and onboard a user into LifeOS — the Life Operating System (current state → ideal state via TELOS + the Algorithm). The agentic installer detects your OS + harness, wires hooks with permission, scaffolds your USER tree, pulls in sources you provide, and runs the TELOS / current→ideal interview that seeds your Pulse dashboard. USE WHEN install LifeOS, set up LifeOS, lifeos setup, lifeos-setup, lifeos interview, onboard me, run the interview, integrate LifeOS into my harness, update LifeOS, uninstall LifeOS, first-time setup, lifeos doctor, check my install, what capabilities are broken. NOT FOR building or cutting a LifeOS release (private release tooling), editing TELOS after onboarding (use Telos / Interview), or LifeOS system maintenance (use the private maintenance skill).
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
The install + onboarding surface for LifeOS — the Life Operating System. One command takes a stranger on any harness from nothing to a working, personalized install whose Pulse dashboard already shows their current state vs ideal state — without making them adopt a whole new harness.
LifeOS is distributed as one self-contained skill — the LifeOS/ directory is the entire distribution. Everything ships inside it: the orchestrator (SKILL.md, Workflows/, Tools/), the whole-system payload under install/, and the one-line bootstrap at install/install.sh. Nothing ships outside the skill — no release-root install.sh, no .claude/ clone.
The primary install is AI-native: give INSTALL.md (served at ourlifeos.ai/install) to your AI and say "install this." LifeOS is AI-native, so the install is too — you hand the doc (or its link) to whatever harness you already use, and your AI installs LifeOS on your OS and harness, with permission at each step. It's the same document a human can read and follow. INSTALL.md opens with a capability gate, drives the install Tools (which run under bun on any OS, not a shell), wires integration per-harness (honest about what each gets), then runs Setup → Interview.
A terminal shortcut stays for Claude Code on macOS/Linux:
curl -fsSL https://ourlifeos.ai/install.sh | bash
Both are served from the skill's own single sources of truth — INSTALL.md at the skill root, install/install.sh for the shell path (which hands off to the agentic /LifeOS setup). Two versions coexist and mean different things: the frontmatter version: is this skill's own component line (bumped by the maintainer-side BumpSkillVersions, which does not ship in the release), while the distribution version — what a user means by "LifeOS 7.x" — is the GitHub release tag and the LIFEOS_RELEASES/<version>/ parent dir. Never read the component line as the release number. The payload (skills, hooks, system prompt, Algorithm, docs, runtime tools) rides along under install/ and is placed during setup, with permission.
| Trigger | Target |
|---|---|
setup, /LifeOS setup, "install LifeOS", "integrate into my harness" | Workflows/Setup.md |
interview, "onboard me", "run the interview", TELOS capture | Workflows/Interview.md |
doctor, "check my install", "what's broken", "what capabilities are live" | run bun <configRoot>/LIFEOS/TOOLS/Doctor.ts (see INSTALL.md) |
update, "update LifeOS", after a version bump | Workflows/Update.md |
uninstall, "remove LifeOS" | Workflows/Uninstall.md |
doctor is the one tool-backed route — it needs no workflow because Doctor.ts is self-describing: it prints the four capability states (live / broken / declined / stale) and the exact fix command for anything broken. Relay its table, offer the fix it names, and honor decline — a declined capability is a legitimate way to run LifeOS, never a defect to nag about.
Default flow (/LifeOS setup): Setup phase (system integration) → transitions into Interview phase (life onboarding). One continuous experience, two clearly-marked phases — setup is logistics, interview is meaning. Setup ALWAYS runs first; hooks must be wired before the interview seeds anything.
Setup (logistics, first). Detect OS + harness → scan for conflicts and surface them → install prerequisites → overlay the system templates → scaffold the USER tree + link it → trust-gated hook install (show the exact change, back up settings.json, wait for yes) → activate the identity imports → verify with two evidence classes. Adapts to OS (macOS/Linux/Windows) and harness (Claude Code / Hermes / Cursor / OpenClaw).
Interview (meaning, second). Name the DA → principal identity → TELOS current state → TELOS ideal state → pull in external sources the user provides (existing notes, configs, exports) to enrich USER context → seed Pulse. By the end, the config tree is populated and Pulse shows real data, not empty scaffolding.
install.sh touches only the LifeOS skill dir; setup writes are existsSync-guarded. Never overwrite or rm a populated dir or a foreign file.settings.json first. Nothing changes without an explicit yes.@-imports).version: is the COMPONENT line, not the release. Claude Code ignores it; the maintainer-side BumpSkillVersions (not shipped) maintains it at the source repo. The DISTRIBUTION version is the tag + LIFEOS_RELEASES/<version>/ + the install.sh fetch.install.sh is non-destructive by design. It installs only the LifeOS skill and backs up only a prior LifeOS skill — never the user's other skills, hooks, or config. The whole point is "bolt on, don't take over.".toml, never .yaml. LifeosConfig.ts reads TOML; the legacy .yaml template was retired 2026-06-19.install.sh drops the skill, then /LifeOS setup runs: detect env, surface conflicts, wire hooks with permission, scaffold the USER tree, then roll into the interview.Doctor.ts, relay the capability table, offer the fix command for anything broken.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Compare a component's own design needs with the goals of the larger system through three structured passes. The result identifies conflicts, recommends an appropriate scope, and assesses whether the proposed design fits the whole.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Find quotes that fit a text’s themes, with attribution and a short reason for each suggestion. Add sourced quotes, research thinkers, and organize a quote collection by theme and usage history to avoid repetition.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Collect social posts, business listings, and product reviews through Apify actors, ready-made data collection tools. Filter results by date, rating, or engagement in code before sending relevant records to the AI for research or lead generation.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Create blog illustrations, technical diagrams, comparisons, comics, and icons through workflows tailored to each format. The skill guides composition, color, and model selection, then stages generated images for review before they are used in a project.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Find arXiv papers by topic, research category, or paper ID. Retrieve titles, authors, abstracts, and links, check new submissions, and add AlphaXiv's AI-generated overviews when available to help decide which papers to read.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Clean spoken recordings by transcribing words, identifying filler and false starts, and joining cuts with short audio fades. Preview proposed edits, reduce breaths, repair noise-gate clicks, and optionally use Cleanvoice for additional cloud processing.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.