Search: "life"

Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".

Guide for creating and writing Expo native modules and views using the Expo Modules API (Swift, Kotlin, TypeScript). Covers module definition DSL, native views, shared objects, config plugins, lifecycle hooks, autolinking, and type system. Use when building or modifying native modules for Expo. Not for migrating an existing Swift module from the definition DSL to the Expo Modules API 2.0 macros; use expo-migrate-module (from the expo-experiments plugin) for that.

29 production-ready scripts for iOS app testing, building, and automation. Provides semantic UI navigation, build automation, accessibility testing, and simulator lifecycle management. Optimized for AI agents with minimal token output.

Publication-grade medical prediction workflow with 33 fail-closed gates covering data leakage, calibration, fairness, TRIPOD+AI/PROBAST+AI compliance, and full model lifecycle governance.

Design and draft lifecycle email sequences such as welcome, onboarding, nurture, re-engagement, and upgrade flows. Use when defining triggers, sequence maps, email copy, and performance metrics. Produce file-first outputs under scripts/marketing/<slug>/ and align with product marketing context.

A personal decision engine with 16 independent AI agents, checks and balances, and swappable cultural themes. Covers relationships, finance, learning, execution, risk control, health, and infrastructure. Use when facing complex personal decisions (career change, investment, entrepreneurship, relocation, life planning), needing multi-angle analysis, periodic reviews, or systematic life management. Trigger keywords: analyze, plan, multi-angle, review, start session, debate. Even without explicit keywords, suggest this skill whenever multi-dimensional thinking or major decisions are involved. Not for simple Q&A, translation, or single-step tasks.

Use this skill to prepare onboarding and lifecycle email for new and dormant hosted sign-ups in prepare-and-approve mode: a guided first-value message for a fresh sign-up, an activation nudge for someone who connected but has not run a report, and a re-engagement draft for a dormant account. It prepares Gmail drafts only; it never sends. Distinct from the agency `client-onboarding` skill, which records a client's advisory strategy. Trigger on: "prepare onboarding emails", "draft activation nudges", "welcome new sign-ups", "re-engage dormant hosted users", "run the onboarding loop".

AI that manages all life.

The safety brake for naked AI coding. A deterministic governance layer that lets N coding agents concurrently mutate one repo — via 5D CID identity, a 7-stage lifecycle, SHA256-anchored closure evidence, and atom maps that retire legacy modules through a gated replacement lifecycle.

Flux Cloud/FluxOS AI toolkit: Claude & Codex skills plus a Flux-tuned MCP server for safe, deterministic node/app API workflows (v8 specs, signing, lifecycle, logs/files, endpoint discovery)

X future agent for autonomous life