「standard」の検索結果

Create high-quality, secure, and performance-optimized Containerfiles (Dockerfiles) following best practices for multi-architecture builds, OpenShift/Kubernetes compatibility, and BuildKit cache optimization. Use when the user wants to: (1) create a new Containerfile or Dockerfile for any project (Python, Rust, Go, Node.js, .NET, or any language), (2) containerize an application with multi-stage builds, (3) optimize an existing Containerfile for security, performance, or image size, (4) review or improve container image build practices, (5) set up BuildKit cache mounts for package managers, (6) create OpenShift-compatible container images with non-root users and arbitrary UID support, (7) write a .dockerignore file, or (8) apply OCI LABEL standards.

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 markdown files against formatting standards. Auto-detects and installs markdownlint-cli if missing. Checks project config or falls back to sensible defaults. Supports auto-fix mode. Use when creating or modifying markdown files, validating documentation, or enforcing markdown conventions.

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。

Prepares Go applications to work effectively with AI coding agents. Use when setting up a new Go project or retrofitting an existing one to ensure: structured JSON logging (slog/Zap/ZeroLog/Logrus), machine-readable command output, thorough golangci-lint configuration, non-interactive CLI design with --yes flags, structured error handling with meaningful exit codes, proper context.Context propagation, graceful shutdown, health check endpoints, and a standardized Makefile. Triggers when a user asks to make their Go app "agent-ready," "AI-friendly," wants to improve agent tooling/observability in a Go project, or needs to audit an existing Go project against agent-readiness best practices.

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 creating or updating AGENTS.md files, .github/copilot-instructions.md, or other AI agent rule files, onboarding AI agents to a project, standardizing agent documentation, or when anyone mentions AGENTS.md, agent rules, project onboarding, or codebase documentation for AI agents.

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。

Audit a resume builder or optimization tool for ATS compatibility, keyword matching accuracy, formatting standards, achievement quantification, skill extraction, and job-description alignment scoring. Use when reviewing resume software, career platforms, applicant tracking integrations, CV generators, or job application tools.

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。

Audit a housing affordability system -- evaluate rent burden calculation accuracy (30% and 50% thresholds), area median income modeling with HUD Income Limits and family size adjustments, Fair Market Rent and SAFMR tracking, payment standard administration, utility allowance schedules.

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。

Audit a rehabilitation recovery tracking system -- evaluate standardized outcome instruments (FIM, Barthel Index, SF-36, DASH, LEFS, PROMIS), functional assessment scoring accuracy, SMART goal and milestone tracking, regression detection with alert workflows, pain scale calibration (NRS.

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。

Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..

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。

Analyzes asset lifecycle planning systems for capital expenditure forecasting, replacement scheduling, total cost of ownership modeling, depreciation tracking, and facility condition assessments using IFMA standards and Facility Condition Index scoring..

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。

Review clinical data models and APIs for HL7 FHIR conformance, terminology standards, interoperability, and clinical workflow correctness. Triggers: 'check FHIR compliance', 'review clinical data model', 'audit HL7 conformance', 'validate medical terminology codes'.

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。

Analyze carbon accounting and emissions tracking software for Scope 1/2/3 calculation accuracy, GHG Protocol compliance, offset verification, supply chain emissions, reporting standards (CDP, TCFD, GRI, SASB, SEC), reduction target tracking, and audit trail integrity..

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。

Analyze packaging configurations for carton size selection, void fill minimization, palletization efficiency, sustainable materials, and total packaging cost reduction aligned with ISTA and ASTM D4169 standards..

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。

Analyzes apparel demand prediction systems for trend forecasting, size curve optimization, color and style analytics, sell-through rate tracking, and markdown optimization following CPFR collaborative planning and GTIN product identification standards..

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。

Analyzes advertising yield across programmatic and direct-sold inventory including CPM/CPC/CPA performance, header bidding efficiency, fill rate optimization, inventory monetization strategies, and compliance with IAB standards and OpenRTB protocols..

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 a customer health scorecard across usage, engagement, adoption, NPS, support load, and financial risk. Use when user says "health score", "customer health", "build a scorecard", "how healthy is this account", "customer scoring model", "green yellow red", "health dashboard", or "account health framework" - even if they don't say "scorecard" explicitly. Applies to CSMs building account health models or CS leaders standardizing health tracking across the team.

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。

Parse natural-language quantities, units, dates, and ranges ("5'11\"", "1.5 cups", "72 in to cm", "three days ago", "between 5 and 10 kg", "it's hot") into canonical, validated values with issue codes and spans — and humanize them back. Use when a form input, LLM tool schema, MCP handler, or import pipeline takes free-text measurements/units/dates. Covers Standard Schema fields (quantityField/dateField/lingoObject) for the AI SDK and MCP, the headless <lingo-input>, unit conversion, and format/humanize round-trips. Zero-dependency TypeScript, deterministic.

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。

**WORKFLOW SKILL** — Risk awareness before action. USE FOR: assessing risks (security, data integrity, compatibility, operational, reversibility) of any task at variable depth. Accepts weight: Light (quick scan), Standard (dimensional analysis), Deep (full Risk Radar with evidence). Can be invoked multiple times in the same flow with increasing weight. DO NOT USE FOR: penetration testing, compliance audits, static security analysis tools.

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。

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

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。

Run the Yuzu pre-commit/pre-push test pipeline. Compiles HEAD, stands up the previous release, upgrades it, runs the full standard test surface, records every result + sub-step timing into a durable SQLite test-runs DB. Use when the user says "/test" or asks to run the full test pipeline before commit.

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。

Review Yuzu C++ source changes for C++23 correctness, idiomatic standard-library use, ABI boundaries, threading primitives, and cross-compiler portability across GCC, Clang, MSVC, and Apple Clang. Use for any governance Gate 3 review when `.cpp`, `.hpp`, or `.h` files change.

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 this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing.

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。

Configures PromQL-based Service Level Objective (SLO) alerting policies for Google Cloud resources registered in App Hub or individually specified. Generates Terraform output. Use when the user asks to configure an SLO or Service Level Objective. Don't use for standard alerting policies.

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。

Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters. Produces upgrade plans, pre/post-upgrade checklists, maintenance runbooks with gcloud commands, release channel strategy, and troubleshooting guides. Handles node pool upgrade strategies (surge, blue-green), version compatibility, PDB management, and workload-specific concerns (stateful, GPU, operators). Use this skill whenever the user mentions GKE upgrades, Kubernetes version bumps, node pool maintenance, GKE patching, cluster version management, release channel selection, maintenance windows, surge upgrades, stuck upgrades, or any GKE lifecycle management task — even casual mentions like "we need to upgrade our clusters" or "plan our next GKE maintenance" or "our upgrade is stuck." Don't use for GKE cluster creation, application onboarding, general networking/routing setup, or security policy configurations (use gke-basics or relevant GKE skills 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。

Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation).

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。