「dynamic」の検索結果

Makes iOS apps feel premium, polished, and unmistakably native — SF Symbols mastery, SwiftUI spring animations, haptic feedback choreography, blur/vibrancy materials, Dynamic Type, color system design, and the specific spacings and radii Apple uses. This is about TASTE, not syntax. Activate on 'iOS design polish', 'SwiftUI animation', 'SF Symbols', 'haptic feedback', 'premium iOS feel', 'Apple HIG', 'native iOS look', 'Liquid Glass', 'iOS visual design', 'app polish'.

日本語の概要は準備中です。原文の説明を表示しています。

Meta-skill that orchestrates the discourse skill suite: routes between steel-man-argument, socratic-questioning, toulmin-argument-analysis, logical-fallacy-detector, bad-faith-rhetoric-detector, discourse-elision-analyzer, forensic-speech-structure, and productive-discourse-facilitator. Use when analyzing conversations, facilitating discourse, or operating as a dialogue copilot. Maintains mode (silent analysis, coaching overlay, active facilitator) and decides which skills to invoke based on conversation dynamics.

日本語の概要は準備中です。原文の説明を表示しています。

Builds, validates, schedules, and dynamically modifies DAG execution graphs. Decomposes problems into nodes with dependencies, performs topological sorting, detects cycles, resolves conflicts, and schedules wave-based parallel execution. Use when designing a DAG structure, validating dependencies, planning execution order, or modifying a DAG at runtime. Activate on "build DAG", "plan workflow", "DAG dependencies", "topological sort", "schedule execution", "modify DAG", "replan". NOT for executing DAGs (use dag-runtime), validating outputs (use dag-quality), or matching skills to nodes (use dag-skills-matcher).

日本語の概要は準備中です。原文の説明を表示しています。

Architect scalable styling systems with Tailwind v4, CSS Modules, design tokens, dynamic theming, and container queries. Activate on: design tokens, theming system, Tailwind config, CSS architecture, container queries, dark mode. NOT for: component library creation (use design-system-creator), animation systems (use animation-system-architect).

日本語の概要は準備中です。原文の説明を表示しています。

The intelligence layer of WinDAGs. Decomposes natural language tasks into Hierarchical Task DAGs (HTDAGs), matches subtasks to skills, executes waves in parallel, and dynamically expands nodes when complexity exceeds executor capability. Use for 'orchestrate', 'execute DAG', 'parallel agents', 'decompose task', 'coordinate skills'. NOT for single-skill tasks or simple linear workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Decides HOW to mutate a DAG when a node fails, quality is below threshold, or new information changes the plan. Selects from mutation strategies (add node, replace agent, fork paths, loop back, downgrade model) based on failure type, cost budget, and execution history. Activate on "DAG failed how to fix", "mutation strategy", "replan on failure", "adaptive DAG", "recovery strategy", "what to do when node fails". NOT for detecting failures (use dag-quality), executing mutations (use dag-planner), or runtime execution (use dag-runtime).

日本語の概要は準備中です。原文の説明を表示しています。

Design AgentSpeak(L)-style BDI agents with context-guarded plans, selection functions, and intention stacks. Use for interruptible autonomy, agent policy, and multi-agent orchestration in dynamic environments. NOT for simple rule engines, static planners, or centralized workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Automated discovery and matching of agent skills for dynamic task routing and capability assessment

日本語の概要は準備中です。原文の説明を表示しています。

Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.

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Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the gene-independent DNA-damage / G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.

日本語の概要は準備中です。原文の説明を表示しています。

Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.

日本語の概要は準備中です。原文の説明を表示しています。

This skill recommends urgent treatment (within 24–72 hours) of hypercortisolism when life‑threatening complications of Cushing's syndrome such as infection, pulmonary thromboembolism, cardiovascular events, or acute psychosis are present. Trigger phrases include sepsis, PE, chest pain with hemodynamic instability, new‑onset psychosis, or delirium in a patient with known or suspected Cushing's.

日本語の概要は準備中です。原文の説明を表示しています。

Azure App Configuration SDK for Python. Use for centralized configuration management, feature flags, and dynamic settings.

日本語の概要は準備中です。原文の説明を表示しています。

Centralized configuration management with feature flags and dynamic refresh.

日本語の概要は準備中です。原文の説明を表示しています。

A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.

日本語の概要は準備中です。原文の説明を表示しています。

Extract data from websites, including JavaScript-rendered SPAs and dynamic content

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level aerospace propulsion covering gas turbine engines, rocket propulsion, thermodynamic cycles, nozzle design, and propellant chemistry.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level exoplanet science covering detection methods, orbital dynamics, planetary atmospheres, habitability, and the search for biosignatures.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level fluid mechanics covering fluid statics, continuity, Bernoulli, Navier-Stokes, boundary layers, turbulence, pipe flow, and external aerodynamics.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level classical mechanics knowledge. Use when working with Newton's laws, kinematics, dynamics, energy, momentum, rotational motion, oscillations, gravitation, Lagrangian mechanics, or Hamiltonian mechanics. Also use when the user mentions 'force', 'torque', 'momentum', 'energy conservation', 'simple harmonic motion', 'projectile', 'friction', 'center of mass', 'moment of inertia', 'Lagrangian', or 'Hamiltonian'.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level fluid physics knowledge. Use when working with fluid statics, fluid dynamics, Bernoulli equation, viscosity, turbulence, Navier-Stokes equations, boundary layers, vorticity, compressible flow, or surface tension. Also use when the user mentions 'Bernoulli', 'Navier-Stokes', 'Reynolds number', 'turbulence', 'viscosity', 'boundary layer', 'vorticity', 'continuity equation', 'laminar flow', 'pressure', 'buoyancy', or 'surface tension'.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level physical chemistry knowledge. Use when working with thermodynamics, chemical kinetics, quantum chemistry, statistical mechanics, spectroscopy, electrochemistry, or surface chemistry. Also use when the user mentions 'Gibbs energy', 'equilibrium constant', 'reaction kinetics', 'rate law', 'activation energy', 'Arrhenius', 'partition function', 'Schrodinger equation', 'molecular orbital', 'electrochemistry', 'Nernst equation', or 'surface adsorption'.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level plasma physics knowledge. Use when working with plasma state, Debye shielding, plasma oscillations, magnetohydrodynamics, plasma confinement, fusion plasmas, space plasmas, plasma waves, or plasma instabilities. Also use when the user mentions 'plasma', 'Debye length', 'plasma frequency', 'MHD', 'magnetic confinement', 'tokamak', 'plasma instability', 'Alfven wave', 'Langmuir probe', 'ionosphere', or 'solar wind'.

日本語の概要は準備中です。原文の説明を表示しています。

Load this skill whenever the project contains dynamic content updates, status messages, alerts, notifications, loading indicators, or any use of aria-live, role="status", role="alert", or role="log". Under no circumstances add or modify live-region markup without applying these rules. Prioritize correct politeness levels and avoid redundant announcements. Never use a fixed-delay clear-and-reinsert workaround — no standard guarantees it works.

日本語の概要は準備中です。原文の説明を表示しています。