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Verify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"

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。

Manage Azure DevOps resources via CLI including projects, repos, pipelines, builds, pull requests, work items, artifacts, and service endpoints. Use when working with Azure DevOps, az commands, devops automation, CI/CD, or when user mentions Azure DevOps CLI.

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。

Manage Azure Container Registry via the az acr CLI including registries, images, cloud builds, ACR Tasks, authentication, tokens, geo-replication, and networking. Use when working with ACR, az acr commands, pushing/importing/purging container images in Azure, or when the user mentions Azure Container Registry.

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 when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.

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。

Setup and initialization guide for developing AWS CDK (Cloud Development Kit) applications in Python. This skill enables users to configure environment prerequisites, create new CDK projects, manage dependencies, and deploy to AWS.

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。

Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize 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。

Perform an AWS Well-Architected Framework review of the current workload IaC and architecture, generating findings and GitHub issues for improvements.

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。

Query AWS resources using natural language. Covers EC2, S3, RDS, Lambda, ECS, EKS, Secrets Manager, IAM, VPC, networking, messaging, and more. Strictly read-only — no writes, deletes, or mutations.

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。

Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.

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。

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

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 a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine.

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。

Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails.

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 when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

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。

Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.

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。

Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational 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。

Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services

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 AWS resources used in the app (IaC files and/or resources in a target account/region) and optimize costs - creating GitHub issues for identified optimizations.

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 tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

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。

Bootstrap and run a lightweight multi-agent development team. Use when starting or adopting a project, planning work, coordinating implementation and optional QA, brainstorming with distinct perspectives, or preserving context across sessions.

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。

Stop coding agents from shipping generic UI. Use UIZZE's 800,000+ real web and iOS screens to build product-specific interfaces, define a design contract, cover required states, and run a hard finish gate. Use when designing, implementing, redesigning, critiquing, or pre-ship reviewing a web or iOS interface in Codex, Claude Code, Cursor, Copilot, or another coding agent. Trigger with "anti-ui-slop", "stop UI slop", "ground this UI in real screens", or "run the UI finish gate".

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。

Reusable investigation patterns for AWS CloudWatch: Logs Insights query templates, alarm-to-deployment correlation, blast-radius narrowing decision tree, and PromQL-style metric query patterns for structured incident triage.

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。

Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.

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。

Enforce output quality, evidence verification, and quality gates across security audits. Use this skill when you perform SAST, SCA, threat modeling, or security code reviews. Use this skill to verify code locations and taint traces for all findings. Use this skill to prevent the suppression of valid security findings. Use this skill to evaluate reports against quality thresholds (score ≥ 8/10) before delivery.

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。