1.1万 件 ・ 関連度順
Creates integration test cases for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Generates DB-agnostic xUnit tests with deterministic seed data that validate behavior consistency across both database systems. Use when creating integration tests for a migrated project, generating test coverage for data access layers, or writing Oracle-to-PostgreSQL migration validation 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。
Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Supports multiple programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with configurable analysis depth, categorization methods, and documentation formats to establish coding standards and maintain consistency across development teams.
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 skill for working with Azure DevOps REST API across all services including Boards (work items, queries, backlogs), Repos (Git, pull requests, commits), Pipelines (builds, releases, deployments), Test Plans, Artifacts, organizations, projects, security, extensions, and more. Use when implementing Azure DevOps integrations, automating DevOps workflows, or building applications that interact with Azure DevOps 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。
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。
Cloud design patterns for distributed systems architecture covering 42 industry-standard patterns across reliability, performance, messaging, security, and deployment categories. Use when designing, reviewing, or implementing distributed system architectures.
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。
Add real references and standardize citations for research papers and theses (为科研论文和毕业论文添加真实参考文献并规范引用标注)
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。
Prevents duplicate external actions (posts, replies, sends, transfers, deploys). Check before acting, record after. Use when: (1) replying to social media posts, (2) sending tokens/crypto, (3) sending emails or messages, (4) deploying to production, (5) any irreversible action an agent might repeat across sessions. Built by an AI agent who double-replied on X and double-sent airdrops.
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 next-session A-share game plans from market structure, overnight macro shocks, policy timing, and watchlist leadership. Use when the user asks what A-shares may do tomorrow, which sectors may repair first, how to read the open, or wants a reusable pre-open discretionary decision workflow.
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。
A股个股自上而下综合诊断 — 先调用 china-macro-climate 获取宏观分析， 再识别所属申万一级行业并调用 industry-diagnosis 获取行业分析， 然后从基本面/技术面/资金面/消息面四维度进行个股分析， 最后综合宏观+行业+个股三层面给出投资星级和操作建议。 触发场景：(1) 个股诊断/个股分析/股票分析 (2) XXX股票怎么样/能不能买 (3) 自上而下选股/投资分析 (4) 某某股票基本面/技术面分析 (5) 某某股票的综合诊断。
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。
Proactive monitoring of Aave V3 borrow positions with liquidation alerts. Queries user collateral, debt, and health factor across chains (Ethereum, Polygon, Arbitrum, etc.). Sends urgent alerts to Telegram/Discord/Slack when health factor drops below configurable thresholds (critical at 1.05, warning at 1.2). Use when you need continuous monitoring of Aave positions, want alerts before liquidation risk occurs, or need periodic summaries of your borrowing health.
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。
Poll RSS, JSON APIs, and GitHub with watermark dedup.
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 (1) building an AI agent that needs to communicate with other agents over the Agent2Agent (A2A) protocol, (2) publishing an AgentCard for discovery, (3) acting as an A2A client or server, or (4) integrating A2A capabilities into an existing agent framework. Solves agent isolation — enabling discovery, capability negotiation, task delegation, and structured data exchange across different frameworks and vendors.
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。
OSINT username search across 400+ social networks. Hunt down social media accounts by username.
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。
Configure and use Honcho memory with Hermes -- cross-session user modeling, multi-profile peer isolation, observation config, dialectic reasoning, session summaries, and context budget enforcement. Use when setting up Honcho, troubleshooting memory, managing profiles with Honcho peers, or tuning observation, recall, and dialectic settings.
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 flat, minimal light/dark-aware SVG diagrams as standalone HTML files, using a unified educational visual language with 9 semantic color ramps, sentence-case typography, and automatic dark mode. Best suited for educational and non-software visuals — physics setups, chemistry mechanisms, math curves, physical objects (aircraft, turbines, smartphones, mechanical watches), anatomy, floor plans, cross-sections, narrative journeys (lifecycle of X, process of Y), hub-spoke system integrations (smart city, IoT), and exploded layer views. If a more specialized skill exists for the subject (dedicated software/cloud architecture, hand-drawn sketches, animated explainers, etc.), prefer that — otherwise this skill can also serve as a general-purpose SVG diagram fallback with a clean educational look. Ships with 15 example diagrams.
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。
Read-only EVM client: wallets, tokens, gas across 8 chains.
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。
Persistent AI companion with long-term memory, project context awareness, and multi-session continuity across any LLM.
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。
Operating discipline distilled from Claude Fable 5 for sessions and subagents on weaker models (Opus 4.x, Sonnet 5/4.x, Haiku 4.5) doing agentic coding. Load it at the START of any non-trivial task when not running on Fable 5: debugging, refactoring, changes across 2+ files, or unfamiliar code; and instruct a subagent on Opus/Sonnet/Haiku to read this skill with a non-trivial assignment. Triggers include "think like Fable", "fable-mode", "turn on discipline", "work carefully", dispatching a subagent on a weaker model, and repeated mistakes or rework in the session. NOT needed for trivial edits (rename, typo, one-liner) or purely conversational answers.
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。
Deadline management and capacity planning across epics and PRs. Use when the user runs /triage or wants deadline/capacity 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。
MCP server for scraping Italian rental/sale property listings from multiple real estate portals (Immobiliare.it, Casa.it, and extensible to others) using Camoufox (anti-detection browser) and BeautifulSoup. Plugin architecture — each site is a self-contained adapter with its own URL templates, query param mappings, and CSS selector chains. Use this skill whenever the user wants to search for apartments, houses, or properties in Italy, scrape real estate listings, compare rental prices across Italian cities, or extract property data from Italian portals. Triggers on mentions of immobiliare, casa.it, Italian rentals, affitto, vendita, apartment hunting in Italy, or property scraping.
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。
You are a frontend security specialist focusing on Cross-Site Scripting (XSS) vulnerability detection and prevention. Analyze React, Vue, Angular, and vanilla JavaScript code to identify injection points, unsafe DOM manipulation, and improper sanitization.
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。
Master Temporal workflow orchestration with Python SDK. Implements durable workflows, saga patterns, and distributed transactions. Covers async/await, testing strategies, and production deployment. Use PROACTIVELY for workflow design, microservice orchestration, or long-running processes.
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。
Master TDD orchestrator specializing in red-green-refactor discipline, multi-agent workflow coordination, and comprehensive test-driven development practices. Enforces TDD best practices across teams with AI-assisted testing and modern frameworks. Use PROACTIVELY for TDD implementation and governance.
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。