「soft」の検索結果

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

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。

Plan, create, and configure production-ready Azure Kubernetes Service (AKS) clusters. Covers Day-0 checklist, SKU selection (Automatic vs Standard), networking options (private API server, Azure CNI Overlay, egress configuration), security, and operations (autoscaling, upgrade strategy, cost analysis). WHEN: create AKS environment, provision AKS, enable AKS observability, design AKS networking, choose AKS SKU, secure AKS, optimize AKS, AKS spot nodes, AKS cluster-autoscaler, rightsize AKS pod, pod rightsizing, over-provisioned AKS pod, pod resource requests and limits, Vertical Pod Autoscaler, VPA recommendations.

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。

Apply IRQL graph functions to KQL or IRQL query results for Kusto Explorer visualization. Generates Lift_To_Graph mappings and composes Graph_Render_View, Graph_Fold_By_Property, Extract_Node_*, Enrich_Node_*, and Enrich_Graph_* calls. Accepts a supplied query or limited basic natural-language source request; it is not a general natural-language-to-KQL/IRQL skill. WHEN: Lift_To_Graph, Graph_Render_View, Graph_Fold_By_Property, IRQL graph enrichment, graph mapping for existing query results, icon-decorated graph, fold graph nodes. Use azure-kusto-graph for native make-graph analysis, graph-match, shortest paths, components, or persistent graphs.

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。

Assess and migrate cross-cloud workloads to Azure with reports and code conversion. Supports Lambda→Functions, Beanstalk/Heroku/App Engine→App Service, Fargate/Kubernetes/Cloud Run/Spring Boot→Container Apps. WHEN: migrate Lambda to Functions, AWS to Azure, migrate Beanstalk, migrate Heroku, migrate App Engine, Cloud Run migration, Fargate to ACA, ECS/Kubernetes/GKE/EKS to Container Apps, Spring Boot to Container Apps, cross-cloud migration.

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。

Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.

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 and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric 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。

Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.

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。

Compose IRQL (Incident Response Query Language) queries for Kusto cybersecurity investigations. Translates natural language hunting questions into composable IRQL pipelines using Get_*, Extract_*, and Enrich_* functions. WHEN: IRQL query, security hunt, threat hunting KQL, incident response query, compose hunting pipeline, failed logins, phishing investigation, lateral movement, process execution, file creation events.

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。

Gate a pitch against one journalist at a time. Runs the pair through proven media-relations checks (last-10-bylines audit, 90-day topic sweep, beat-vs-angle-vs-one-off, the 5 forms of journalism, source-mirror, stated-preferences, database triangulation) and returns fit, soft-fit, no-fit, or unknown with a real recent anchor and specific edits.

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。

Breaks down complex software, writing, or research tasks into small, atomic, independently completable units with dependency graphs and milestone breakdowns. Use when the user asks to plan a project, decompose a feature, create subtasks, split up work, or needs help organizing a large piece of work into a step-by-step plan. Triggered by phrases like "break down", "decompose", "where do I start", "too big", "split into tasks", "work breakdown", or "task list".

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。

Create a qualitative risk register and mitigation plan using a Probability x Impact matrix. Use when a project needs structured risk identification, scoring, ownership, and response planning.

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 a structured Azure incident response workflow for triage, diagnosis, mitigation, and root cause analysis. Use when operations or security teams need guided incident handling for Azure service symptoms.

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。

Generate synthetic datasets in a Jupyter notebook after the dataops synthetic-data preflight passes. Use when creating new synthetic data or preparing a guarded local replacement candidate from an approved source.

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。

Export Design Thinking artifacts to a FigJam board or Figma Design file through the Figma MCP server. Use when a team wants collaborative visual review of Method 1, 3, 4, 5, or 6 artifacts, or accepts a DT Coach board-export offer.

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。

Stage user-selected paths, confirm the exact staged set, and create one local Conventional Commit, or generate a commit message for staged changes without committing. Use when you want a guarded commit or a ready-to-paste message.

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 Git configuration with one read-only baseline command, then propose confirmed, non-destructive fixes for identity, editor, and diff and merge tooling, with signing and safe.directory help only on request. Use when setting up or checking Git on a workstation.

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, refresh, report, or probe an accessibility coverage matrix across criteria, surfaces, and evidence methods. Use when assessing coverage with the accessibility runtime harness and generated evidence bundle.

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。

Coordinate Git merge, rebase, and rebase --onto workflows with conflict resolution, optional review pauses, and a completion summary. Use when integrating a branch locally and resolving conflicts without pushing.

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 one independent Council critique against engagement-report research evidence. Use as the manual separate-session fallback when independent critic agents are unavailable.

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。

Create or update project cspell configuration by resolving the loaded config, active dictionaries, curated words, ignore paths, and validation evidence. Use when spell-check configuration needs project words or ignores.

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。

Challenge a confirmed task, decision, plan, or artifact through adaptive skeptical questions. Use when you need to expose assumptions before acting.

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。

Consolidated Responsible AI standards reference: NIST AI RMF 1.0, AI STRIDE threat-modeling overlay, EU AI Act risk tiers, and an open-standards catalog with phase mapping

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。

Format specifications and data contracts for the security reviewer orchestrator and its subagents.

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。

OWASP Top 10 for Web Applications (2025) knowledge base for identifying, assessing, and remediating web application security risks.

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。