「fea」の検索結果

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration 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。

This skill should be used when working on Nuxt projects (v3+). Use it for building Vue applications with Nuxt's file-based routing, server-side rendering, and auto-import features. Trigger when working with .vue or .ts files in Nuxt directories (pages/, server/, composables/, middleware/), nuxt.config.ts, or when the project contains a nuxt dependency in package.json. Also trigger for questions about Nuxt concepts like composables, auto-imports, server routes, SSR/SSG patterns, or file-based routing.

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。

PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.

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。

PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).

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 high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk 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。

Launch and automate VS Code (Code OSS) using agent-browser via Chrome DevTools Protocol. Use when you need to interact with the VS Code UI, automate the chat panel, test UI features, or take screenshots of VS Code. Triggers include 'automate VS Code', 'interact with chat', 'test the UI', 'take a screenshot', 'launch Code OSS with debugging'.

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。

Discovers and integrates third-party APIs using the context-matic MCP server. Uses `fetch_api` to find available API SDKs, `ask` for integration guidance, `model_search` and `endpoint_search` for SDK details. Use when the user asks to integrate a third-party API, add an API client, implement features with an external API, or work with any third-party API or SDK.

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 skill for writing FreeCAD Python scripts, macros, and automation. Use when asked to create FreeCAD models, parametric objects, Part/Mesh/Sketcher scripts, workbench tools, GUI dialogs with PySide, Coin3D scenegraph manipulation, or any FreeCAD Python API task. Covers FreeCAD scripting basics, geometry creation, FeaturePython objects, interface tools, and macro 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。

This workflow guides you through a systematic approach to identify missing features, prioritize them, and create detailed specifications for implementation.

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 get context about Fabric Lakehouse and its features for software systems and AI-powered functions. It offers descriptions of Lakehouse data components, organization with schemas and shortcuts, access control, and code examples. This skill supports users in designing, building, and optimizing Lakehouse solutions using 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。

Provides expert guidance on Development Containers (devcontainers) — creating, configuring, and optimising containerised development environments using the Dev Container Specification. This skill should be used when users ask about devcontainer.json, .devcontainer setup, Dev Container Features or Templates, pre-building images, multi-container workflows, Docker-in-Docker, cloud development environments (Codespaces, DevPod), or troubleshooting container performance and permission issues.

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 GitHub Pull Request for feature request from specification file using pull_request_template.md template.

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 GitHub Issues for unimplemented requirements from specification files using feature_request.yml template.

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 new implementation plan file for new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.

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。

Issue Planning and Automation prompt that generates comprehensive project plans with Epic > Feature > Story/Enabler > Test hierarchy, dependencies, priorities, and automated tracking.

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。

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。

Primary accessibility skill for VS Code. REQUIRED for new feature and contribution work, and also applies to updates of existing UI. Covers accessibility help dialogs, accessible views, verbosity settings, signals, ARIA announcements, keyboard navigation, and ARIA labels/roles.

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。

Agents workbench layout — covers the fixed layout structure, grid configuration, part visibility, editor modal, titlebar, sidebar footer, and implementation requirements. Use when implementing features or fixing issues in the Agents workbench layout.

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。

Delegate coding to xAI Grok Build CLI (features, PRs).

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。

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

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。

Audio spectrograms/features (mel, chroma, MFCC) via 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。

Throwaway experiments to validate an idea before build.

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。

GPU-accelerated terminal emulator with AI-native and Web3-native features built on wgpu+WASM.

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。