「sic」の検索結果

Use when forensically auditing a Claude Code skill/agent/command/workflow library against RULESET.md by a fixed mechanical protocol — probing every file against the mechanically-checkable rules and reporting CONFORMS / VIOLATES / UNVERIFIABLE / N-A counts with quoted evidence. It casts NO judgment and emits NO pass/fail verdict; counts are the headline. Triggers on "investigate the library", "audit against RULESET", "find every violation", "forensic library audit", "evidence-only check". Not for routing/quality/single-responsibility judgment — use skill-library-review. Not the full sharded sweep — use the audit-library command.

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 performant animation systems with Framer Motion, GSAP, View Transitions API, and spring physics. Activate on: page transitions, micro-interactions, scroll animations, layout animations, spring physics. NOT for: CSS-only hover effects (use css-in-js-architect), video/canvas rendering (use creative-coding-expert).

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。

Assesses genetic health of populations for conservation with Ne estimation across time horizons (LDNe NeEstimator V2 option-file API + SNeP physical-linkage correction; recent trajectory via GONE/GONE2; deep history via Stairway Plot 2 / dadi / fastsimcoal2 / PSMC), F-statistics, runs of homozygosity binned by length class to date inbreeding, genetic-load decomposition (Bertorelle 2022 realized vs masked), the modern 100/1000 Ne rule (Frankham 2014), Ne/Nc 2-6 orders of magnitude in marine fish (Hauser & Carvalho 2008), tree-sequence forward simulations (SLiM 4 + pyslim + tskit), and the Sukumaran-Knowles caveat against MSC methods for management-unit definition. Use when estimating Ne by time horizon, detecting inbreeding via F_ROH, decomposing genetic load, justifying conservation thresholds, distinguishing ESU/MU/DPS, configuring NeEstimator V2, or correcting LDNe physical linkage.

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。

AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.

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 nuclear energy covering fission reactor physics, reactor types, safety systems, nuclear fuel cycle, waste management, and advanced reactor concepts.

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 VLSI design covering CMOS logic, custom layout, standard cell design, physical design flow, DRC, LVS, and advanced process nodes.

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 fusion energy covering plasma physics fundamentals, confinement methods, tokamak design, ITER, private fusion ventures, and the path to commercial fusion power.

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。

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 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 general relativity knowledge. Use when working with curved spacetime, Einstein field equations, geodesics, black holes, gravitational waves, cosmology, Schwarzschild metric, or tensor calculus. Also use when the user mentions 'Einstein field equations', 'curved spacetime', 'geodesic', 'black hole', 'event horizon', 'Schwarzschild', 'gravitational waves', 'spacetime curvature', 'Riemann tensor', 'metric tensor', 'cosmological constant', or 'gravitational lensing'.

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 nuclear physics knowledge. Use when working with nuclear structure, radioactive decay, nuclear reactions, fission, fusion, binding energy, nuclear models, radiation, or nuclear applications. Also use when the user mentions 'radioactive decay', 'half life', 'binding energy', 'fission', 'fusion', 'alpha decay', 'beta decay', 'gamma decay', 'nuclear reaction', 'cross section', 'Q value', 'nuclear reactor', or 'radiation dose'.

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 particle physics knowledge. Use when working with the Standard Model, quarks, leptons, bosons, fundamental forces, Feynman diagrams, quantum field theory, particle accelerators, or particle detectors. Also use when the user mentions 'Standard Model', 'quark', 'lepton', 'boson', 'Higgs', 'gluon', 'neutrino', 'antimatter', 'Feynman diagram', 'QCD', 'QED', 'electroweak', 'LHC', or 'particle accelerator'.

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 SwiftUI guidance for macOS apps — covers writing and reviewing code with runtime-level understanding of observation, concurrency, performance, and platform integration. Use when user asks to "build a SwiftUI view", "review my SwiftUI code", "fix observation issues", "bridge AppKit", "architect state management", "debug view updates", or works on any macOS SwiftUI project — building features, reviewing existing code, debugging view updates or performance, fixing concurrency issues, architecting state management, bridging AppKit, or making design decisions. Do NOT use for iOS/iPadOS-only SwiftUI, UIKit bridging, or basic Swift language questions. Focuses on non-obvious traps and deep patterns, not basics.

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。

Use when a release review needs machine-derived evidence from git history — hotspot risk and change-coupling analyzers. Triggers on 'hotspot', 'what changes together', 'release forensics'.

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。

Quando o usuário quer aplicar princípios psicológicos, modelos mentais ou ciências comportamentais ao marketing. Também use quando o usuário mencionar 'psicologia', 'modelos mentais', 'viés cognitivo', 'persuasão', 'ciência comportamental', 'por que as pessoas compram', 'tomada de decisão' ou 'comportamento do consumidor'. Esta skill fornece 70+ modelos mentais organizados para aplicação em marketing.

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。

Build UI interactions whose motion comes from a physical model instead of durations and easing curves. Turn a feel described in words ("a toggle that feels heavy", "a drawer with a magnetic snap", "a card you throw into a corner", "a knob with heavy detents", "a sticky slider") into a production component driven by mass, stiffness, damping and force fields (magnets, friction, walls), on a line, in a plane or around a dial, plus a test rig that plots position, velocity and the force field, overlays the model's prediction on the measured motion, and exports the same spring to Framer Motion, react-spring, SwiftUI, Compose or CSS linear(). Use this whenever someone asks for an animation, transition, spring, gesture, drag, flick, snap points, bottom sheet, toggle, slider, carousel or any micro-interaction that should "feel" a certain way, or wants to tune or explain a spring, even if they never say "physics".

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。

Validate and implement Sinclair ZX Spectrum 48K ROM-visible behavior in the EMULATORS repository, including reset and restart vectors, IM1/NMI handling, keyboard scanning and repeat, beeper and tape routines, screen/printer output, channels and streams, BASIC tokenization and execution, expression evaluation, memory movement, system variables, calculator stack, floating-point formats, ROM traps, localized ROM selection, and firmware/hardware timing contracts. Use when Codex reviews or edits ZX Spectrum ROM loading, KERNAL-style traps, keyboard, tape, screen, printer, BASIC files, tokens, system variables, startup, interrupts, or compatibility tests.

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。

吉里吉里Z (kirikiri Z) 本体クラス API のリファレンス。TJS2 で吉里吉里Z 上のスクリプトを書く、レビューする、デバッグするときに使う。Layer / Window / Bitmap / System / Storages / Font / Plugins / Timer / Debug / AsyncTrigger / Scripts / BinaryStream / Matrix32 / Matrix44 / Rect / ImageFunction のコア API、サウンド系 (WaveSoundBuffer / SoundBuffer / VideoOverlay)、DrawDevice (BasicDrawDevice / SDLDrawDevice / OGLDrawDevice / GPUDrawDevice / NullDrawDevice)、OpenGL 描画系 (Canvas / Texture / ShaderProgram / Offscreen / VertexBinder / VertexBuffer)、および主要プラグイン提供クラス (HttpRequest / GdiPlus.* / WIN32Dialog / CSVParser / LineParser / Process / Pad / MenuItem / Unzip / Zip / PSD / SimpleHTTPServer) を網羅。**呼び出されたら必ず「共通パターン」と「クロスカッティング概念」を確認し、必要な詳細クラスは doc/reference/*.md を Read しに行くこと。** TJS2 言語そのものや組み込みクラス (Array / Dictionary / Math 等) は別 skill (`tjs2`) を参照。エンジン内部構造 (C++ 実装、レンダリングパイプライン詳細) は対象外。

Detects rootkit presence on compromised systems by identifying hidden processes, hooked system calls, modified kernel structures, hidden files, and covert network connections using memory forensics, cross-view detection, and integrity checking techniques. Activates for requests involving rootkit detection, hidden process discovery, kernel integrity checking, or system call hook analysis.

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 covers detecting sophisticated cyber-physical attacks that follow the Stuxnet attack pattern of modifying PLC logic while spoofing sensor readings to hide the manipulation from operators. It addresses PLC logic integrity monitoring, physics-based process anomaly detection, engineering workstation compromise indicators, USB-borne attack vectors, and multi-stage attack chain detection spanning IT-to-OT lateral movement through to process manipulation.

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。

Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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 covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.

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。