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概要と使いどころ
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP 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。
When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.
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 evaluating startups or growth companies through a Sequoia-style lens: founder quality, market size, product-market fit, distribution, and long-term company building.
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 evaluating startups through a Founders Fund-style lens: contrarian conviction, hard tech, bold product ambition, non-consensus markets, and high-upside company building.
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 is building a fundraising / investor pitch deck — seed, Series A / B / C, convertible note, SAFE round, strategic raise. Trigger on: 'pitch deck', 'investor deck', 'Series A deck', 'Series B deck', 'Series C deck', 'fundraising deck', 'seed pitch', 'VC deck', 'raising capital', 'term sheet presentation'. Output is a single .pptx. This skill is a scene layer on top of officecli-pptx — inherits every pptx v2 rule (visual floor, grid, palettes, connector canon, Delivery Gate). DO NOT invoke for a generic board review, sales deck, all-hands, or product launch — route those to officecli-pptx base.
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。
Lookup accommodations by city from the bundled dataset. Use this skill when you need to recommend places to stay in a given city or filter lodging options before building an itinerary.
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。
Retrieve attractions by city from the bundled dataset. Use this skill when surfacing points of interest or building sightseeing suggestions for a destination.
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。
Core building blocks of Suricata signatures and multi-condition DPI logic
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。
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
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 spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and pivot tables. When Claude needs to work with spreadsheets (.xlsx files) for: (1) Creating new spreadsheets with data and formatting, (2) Reading or analyzing Excel data with pandas, (3) Creating pivot tables programmatically with openpyxl, (4) Building multi-sheet workbooks with source data and pivot table sheets, or (5) Any Excel file operations
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 oTP behaviors including gen_server for stateful processes, gen_statem for state machines, supervisors for fault tolerance, gen_event for event handling, and building robust, production-ready Erlang applications with proven patterns.
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 erlang distributed systems including node connectivity, distributed processes, global name registration, distributed supervision, network partitions, and building fault-tolerant multi-node applications on the BEAM VM.
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 erlang's concurrency model including lightweight processes, message passing, process links and monitors, error handling patterns, selective receive, and building massively concurrent systems on the BEAM VM.
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。
Nonlinear optimization with CasADi and IPOPT solver. Use when building and solving NLP problems: defining symbolic variables, adding nonlinear constraints, setting solver options, handling multiple initializations, and extracting solutions. Covers power systems optimization patterns including per-unit scaling and complex number formulations.
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 library for building, validating, visualizing, and serializing dialogue graphs. Use this when parsing scripts or creating branching narrative structures.
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。
DC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks.
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。
Drive feature development using Outside-In TDD with Hexagonal Architecture. Design emerges through inline code, in-memory fakes, interface extraction, and deferred I/O. Use when building features, writing tests, or structuring backend services. Triggers on: TDD, outside-in, hexagonal, ports and adapters, emergent design, acceptance test, component test, walking skeleton, in-memory fakes, component, contract test, adapter, fast tests, sub-second feedback. Language-agnostic (Go, Rust, Python, TypeScript, Java, C#).
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。
Work with Rust async runtimes — Tokio, async-std, executor internals, pinning, wakers, and building high-performance async Rust 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。
Use when starting any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before 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。
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP 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。
Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
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。
Implement Stripe payment processing for robust, PCI-compliant payment flows including checkout, subscriptions, and webhooks. Use when integrating Stripe payments, building subscription systems, or implementing secure checkout flows.
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 Unity ECS (Entity Component System) with DOTS, Jobs, and Burst for high-performance game development. Use when building data-oriented games, optimizing performance, or working with large entity counts.
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。
Coordinate the test-driven development cycle from requirements and failing tests through implementation, refactoring, and validation. Use when building a feature with a structured TDD 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。