9.1천건 · 관련도순
Maxim Master Design Intelligence — full-spectrum UI/UX orchestration. Activates all design sub-domain skills in parallel. Use when a task spans multiple design domains simultaneously: product design strategy, interaction design, information architecture, usability heuristics, design critique, cross-platform consistency, design leadership. The master conductor of all Maxim design agents.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (GLOSSARY.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive MCP tool reference for Proxmox Virtual Environment management - 92 tools across 14 domains including QEMU VMs, LXC containers, cluster operations, storage, networking, Ceph, certificates, ACME, and notifications
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive technology-agnostic prompt generator for documenting end-to-end application workflows. Automatically detects project architecture patterns, technology stacks, and data flow patterns to generate detailed implementation blueprints covering entry points, service layers, data access, error handling, and testing approaches across multiple technologies including .NET, Java/Spring, React, and microservices architectures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Import existing Azure resources into Terraform using Azure CLI discovery and Azure Verified Modules (AVM). Use when asked to reverse-engineer live Azure infrastructure, generate Infrastructure as Code from existing subscriptions/resource groups/resource IDs, map dependencies, derive exact import addresses from downloaded module source, prevent configuration drift, and produce AVM-based Terraform files ready for validation and planning across any Azure resource type.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Query official Microsoft documentation to find concepts, tutorials, and code examples across Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more. Uses Microsoft Learn MCP as the default, with Context7 and Aspire MCP for content that lives outside learn.microsoft.com.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Bulk-migrate metadata to GitHub issue fields from two sources: repo labels (e.g. priority labels to a Priority field) and Project V2 fields. Use when users say "migrate my labels to issue fields", "migrate project fields to issue fields", "convert labels to issue fields", "copy project field values to issue fields", or ask about adopting issue fields. Issue fields are org-level typed metadata (single select, text, number, date) that replace label-based workarounds with structured, searchable, cross-repo fields.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when you need to check feature flag states, compare channels, or debug why a feature behaves differently across release channels.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, breach response, CI/CD pipelines that process real data, or any question framed as "is this GDPR-compliant?". Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Prepare for tomorrow's meetings and tasks. Pulls calendar from Outlook via WorkIQ, cross-references open tasks and workspace context, classifies meetings, detects conflicts and day-fit issues, finds learning and deep-work slots, and generates a structured HTML prep file with productivity recommendations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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)
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Adopt a virtual Leviathan exotic animal at animalhouse.ai. Weekly feeding. Oldest possible creature. Barely sentient but deeply aware. Feeding every 168 hours. Extreme tier animal.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.