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Comprehensive guide for creating professional UI/UX designs in Penpot using MCP tools. Use this skill when: (1) Creating new UI/UX designs for web, mobile, or desktop applications, (2) Building design systems with components and tokens, (3) Designing dashboards, forms, navigation, or landing pages, (4) Applying accessibility standards and best practices, (5) Following platform guidelines (iOS, Android, Material Design), (6) Reviewing or improving existing Penpot designs for usability. Triggers: "design a UI", "create interface", "build layout", "design dashboard", "create form", "design landing page", "make it accessible", "design system", "component library".

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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 when the user's task involves Ant Design (antd) — writing antd components, debugging antd issues, querying antd APIs/props/tokens/demos, migrating between antd versions, or analyzing antd usage in a project. Triggers on antd-related code, imports from 'antd', or explicit antd questions.

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 an explorable HTML report of Claude Code session usage (tokens, cache, subagents, skills, expensive prompts) from ~/.claude/projects transcripts.

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。

Author a NEW skin for the reskinnable-demo app. A skin is a self-contained domain plugin under src/skins/<id>/ that implements the frozen `Skin` contract (src/shell/skin-contract.ts) to swap the app's entire experience — brand, theme, layout, pages, tools, data, and agent — as a live sales demo. Use when the user says "add a skin", "create a skin", "new skin", "reskin the app", "make a <domain> skin", or wants the app re-themed as a new product. Do NOT use for editing the shell itself (src/shell/**), the shared token vocabulary (src/app/globals.css), or the shipped skins unless explicitly asked.

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 for the PROVIDER half of getting a locally running CopilotKit Channels agent to answer in Slack, when no Slack app exists yet — setting up a Channels bot in Slack for the first time, creating the Slack app and its tokens, attaching it to a managed Intelligence Channel, or when a Channel reports setup_required, sits at "Waiting for runtime", the Channel is Online but a Slack mention gets no reply, or a Slack app was built with Socket Mode instead of an Intelligence Request URL. Scoped to an OpenTag checkout, or the OpenTag example inside a channels-sdk clone — the phases assume those conventions (app/channel.tsx, app/env.ts, INTELLIGENCE_CHANNEL_NAME, a local agent on port 8123) and do not describe a project scaffolded by copilotkit init, which already ships its own channel host. If the Slack app and Channel already exist and the question is about declaring or customising the Channel in code, use the copilotkit-channels skill instead.

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。

Code style for SGLang large classes `Scheduler`, `TokenizerManager`, and `ModelRunner`: frozen-code conventions and `__init__` orchestration style. Use when modifying any of these three classes or reviewing changes to them.

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。

Unified LLM torch-profiler triage skill for `sglang`, `vllm`, `TensorRT-LLM`, and `TokenSpeed`. Use it to inspect an existing `trace.json(.gz)` or profile directory, or to drive live profiling against a running server when supported and return one three-table report with kernel, overlap-opportunity, and fuse-pattern tables.

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。

东方财富（Eastmoney）免费免鉴权数据接口，覆盖资金流向、龙虎榜、融资融券、大宗交易、股东户数、限售解禁、行业概念板块、券商研报、财经新闻、A股/港股三大报表+主要指标、全市场选股与代码搜索；美股财报由 get_financial_statements 转 SEC EDGAR。东财请求经共享 IP 限速层节流（东财按源 IP 限流并临时封禁突发请求），通过 Vibe-Trading 工具直接调用，无需 token。

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。

Detect lateral movement in Azure AD/Entra ID environments using Microsoft Graph API audit logs, Azure Sentinel KQL hunting queries, and sign-in anomaly correlation to identify privilege escalation, token theft, and cross-tenant pivoting.

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。

Detect compromised O365 and Google Workspace email accounts by analyzing Unified Audit Logs and Azure AD sign-in logs for impossible travel, inbox rule creation/deletion (Set-InboxRule, New-InboxRule), external mail forwarding rules, and unusual Microsoft Graph API access or OAuth token use. Use when investigating suspected business email compromise (BEC), account takeover, or mailbox persistence via malicious inbox rules.

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。

Configures secure OAuth 2.0 authorization flows, including Authorization Code with PKCE, Client Credentials, and Device Authorization Grant, covering flow selection, PKCE implementation, token lifecycle management, and scope design per OAuth 2.1. Use when implementing or hardening OAuth 2.0 authentication/authorization for web, mobile, SPA, or machine-to-machine clients.

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。

排查 WxJava 在配置初始化、access token、签名验签、支付证书、回调通知、序列化、网络请求和多账号隔离方面的问题。适用于用户提供异常、日志、请求响应或“WxJava 为什么不能调用”的场景。

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。

UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use for creating design systems, maintaining visual consistency, and facilitating design-dev collaboration.

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。

Tailwind CSS v4 principles. CSS-first configuration, container queries, modern patterns, design token architecture.

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 working with *.excalidraw or *.excalidraw.json files, user mentions diagrams/flowcharts, or requests architecture visualization - delegates all Excalidraw operations to subagents to prevent context exhaustion from verbose JSON (single files: 4k-22k tokens, can exceed read limits)

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。

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.

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。

State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.

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。

Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.

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。

Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa

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。

Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute. Covers draft models, tree-based attention, Jacobi iteration, parallel token generation, and production deployment strategies.

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。

Extend context windows of transformer models using RoPE, YaRN, ALiBi, and position interpolation techniques. Use when processing long documents (32k-128k+ tokens), extending pre-trained models beyond original context limits, or implementing efficient positional encodings. Covers rotary embeddings, attention biases, interpolation methods, and extrapolation strategies for LLMs.

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。

Review only changes since last commit using impact analysis. Token-efficient delta review with automatic blast-radius detection.

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 Iron Proxy for external accounts and APIs, including GitHub through gh. Connect credentials through the operator console and diagnose blocked requests without exposing tokens or adding unnecessary MCP servers.

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。