「standard」の検索結果

When setting up telemetry, debugging distributed systems, or standardizing application output.

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 should be used when the user asks to "calculate traffic accident damages", "交通事故の損害額を計算", "損害賠償額を算出", "赤い本基準で計算", "逸失利益を計算", "後遺障害の慰謝料", "過失相殺後の金額", or wants deterministic computation of personal-injury damages under the Red Book (赤い本) standard.

This skill should be used when the user asks to "calculate child support", "養育費を計算", "婚姻費用を計算", "養育費月額", "婚姻費用分担額", "算定表で計算", or wants deterministic computation of child support or marital cost-sharing under the 令和元年改定 standard.

Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.

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。

Pod Security Standards (PSS) define three levels of security policies -- Privileged, Baseline, and Restricted -- enforced by the Pod Security Admission (PSA) controller built into Kubernetes 1.25+. PS

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。

AES (Advanced Encryption Standard) is a symmetric block cipher standardized by NIST (FIPS 197) used to protect classified and sensitive data. bu skill covers implementing AES-256 encryption in GCM m

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。

bu skill covers hardening managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity, RBAC scoping, image admission controls, and runtime security monitoring. It addresses cloud-specific security features including IRSA for EKS, Workload Identity for GKE, and Managed Identities for AKS.

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。

bu skill covers Dağıt:ing AWS Security Hub as a centralized cloud security posture management platform that aggregates Bul:ings from GuardDuty, Denetle:or, Macie, and third-party tools. It details enabling security standards like CIS AWS Foundations Benchmark, configuring automated remediation, and building executive dashboards for compliance tracking across multi-account AWS organizations.

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。

ScalarDBエディション選定エージェント - 対話形式で最適なScalarDBエディション（OSS/Enterprise Standard/Premium）を選定。/select-scalardb-edition で呼び出し。

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".

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。

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

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。

High-performance reinforcement learning framework optimized for speed and scale. Use when you need fast parallel training, vectorized environments, multi-agent systems, or integration with game environments (Atari, Procgen, NetHack). Achieves 2-10x speedups over standard implementations. For quick prototyping or standard algorithm implementations with extensive documentation, use stable-baselines3 instead.

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 validates quantitative targeted metabolomics assays (MRM/SRM on triple-quadrupole, PRM on high-resolution instruments) to report absolute concentrations. Covers the internal-standard strategy (external cal -> global IS -> standard addition -> stable-isotope-labeled IS), weighted calibration judged by back-calculated %RE not R-squared, ion-ratio quantifier/qualifier confirmation, matrix-effect/recovery characterization, and ICH M10 method validation. Use when quantifying a closed panel of known metabolites with units, building or validating an LC-MS/MS assay, choosing an IS or calibration weighting, or judging whether a reported concentration is trustworthy. For untargeted feature detection see metabolomics/xcms-preprocessing; for group statistics see metabolomics/statistical-analysis; for flux/MID/tracing see metabolomics/isotope-tracing.

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。

Assigns honest lipid annotation levels, designs class-based internal-standard quantification, and runs lipid-aware differential and enrichment analysis with lipidr, guarding against in-source-fragment phantoms, sn-position over-claims, and invalid cross-class quantification. Use when naming or canonicalizing lipid species (shorthand separators, Goslin), deciding shotgun vs RP vs HILIC LC-MS, picking internal standards (SPLASH/EquiSPLASH), interpreting MS-DIAL/LipidSearch output, or comparing lipid classes. For general feature detection see metabolomics/xcms-preprocessing and metabolomics/msdial-preprocessing; for non-lipid annotation confidence see metabolomics/metabolite-annotation; for normalization/QC see metabolomics/normalization-qc; for multivariate stats see metabolomics/statistical-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。

Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.

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。

Runs standard-format scenarios through ScenarioRunner — ASAM OpenSCENARIO 1.x (.xosc, via --openscenario, with catalogs and ParameterDeclaration overrides) and OpenSCENARIO 2.0 (.osc, via --openscenario2, the ANTLR/osc2 pipeline). Validates a file against the schema before running, lists the bundled examples, and reports which OSC features ScenarioRunner actually implements. Use when the user asks to "run an xosc", "run an OpenSCENARIO file", "use the OpenSCENARIO standard", "run a .osc / OSC2 scenario", or hands over a scenario file from another tool.

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。

Imports a custom RoadRunner map (FBX geometry + XODR OpenDRIVE) into a CARLA source build as a drivable map — reads the map from the directory the user names, runs CARLA's Import.py to cook the level, Traffic Manager graph and (standard maps only) pedestrian navmesh, and verifies it loads on a server. Handles both standard maps and large tiled maps; large maps get no navmesh, matching upstream CARLA. Use when the user asks to "import a map into CARLA", "add a custom/RoadRunner map", "ingest an FBX+XODR map", "make import", bring in a "large/tiled map", or fix missing walkers / a missing pedestrian navmesh.

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。

Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"

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 knowledge of academic writing standards for peer-reviewed papers, including citation integrity, style compliance, clarity, and scientific writing best practices. Use when reviewing or editing academic manuscripts, papers, or research documentation.

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。

PSR-1 and PSR-12 coding standards knowledge base for PHP 8.5 projects. Provides quick reference for basic coding standard and extended coding style with detection patterns, examples, and antipattern identification. Use for code style audits and compliance reviews.

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。

Three.js (WebGL / WebGPU ベース 3D グラフィクスライブラリ) リファレンス。 Scene, PerspectiveCamera, OrthographicCamera, WebGLRenderer, WebGPURenderer、 BufferGeometry, BufferAttribute, Mesh, Group, InstancedMesh, SkinnedMesh、 MeshStandardMaterial, MeshPhysicalMaterial, ShaderMaterial, node-materials (TSL)、 DirectionalLight, PointLight, SpotLight, AmbientLight、 TextureLoader, GLTFLoader, DRACOLoader, FBXLoader、 AnimationMixer, AnimationClip, AnimationAction, KeyframeTrack、 Vector3, Matrix4, Quaternion, Euler, Color, Raycaster, Box3、 OrbitControls, TransformControls, WebXRManager。

Rust 言語リファレンス。 別名: rustlang, rs (拡張子)、Rust-lang。 TRPL (The Rust Programming Language)、Rust by Example、Reference、 Cargo Book、rustc Book、rustdoc Book、Rustonomicon (Unsafe Rust)、 Edition Guide、Standard Library、Error Index。 所有権、ライフタイム、トレイト、async / await、エラーハンドリング、マクロ。

nuqs (Type-safe URL search params state manager for React / Next.js) リファレンス。 useQueryState, useQueryStates, parsers (parseAsString / parseAsInteger / parseAsBoolean / parseAsArrayOf 等)、 Next.js App Router / Pages Router、SSR、シャロールーティング、history 制御。 createSerializer, createStandardSchemaV1, inferParserType ユーティリティ、URL 長さ制限 (limits)。

Swift Standard Library・Concurrency・プロトコル/ジェネリクス・Observation リファレンス。 async/await、actor、Sendable、Task、TaskGroup、AsyncSequence、AsyncStream、 Equatable、Hashable、Comparable、Codable、Identifiable、Optional、Result、 generics、some/any opaque types、Observable、@Observable、ObservationRegistrar。