NLP

Converts text to speech audio using OpenAI TTS API. Use when users request audio versions of text or want responses read aloud.

コンテキストウィンドウの制約内で情報を最適整理するためのスキル。トークン計測、優先順位付け、圧縮、検証の一連フローを提供する。Anchors:• High Performance Browser Networking / 適用: 計測とレイテンシ意識 / 目的: 予算内最適化• Designing Data-Intensive Applications / 適用: リソース制約下の設計 / 目的: 効率的な構造化• Progressive Disclosure パターン / 適用: 段階的情報開示 / 目的: 過剰読み込みの回避Trigger:Use when optimizing context window usage, measuring token budgets, prioritizing context elements, or applying compression techniques.context window optimization, token budget, context prioritization, compression, summarization

MANDATORY for all naming decisions - variables, functions, files, folders, classes, database tables, routes, CSS classes. Must be followed when creating or renaming any identifier. Non-negotiable baseline for consistent, readable names across all languages and contexts.

Structural code pattern search and refactoring using ast-grep (sg). Use for finding functions, classes, methods, imports, or any code structure patterns. Supports syntax-aware analysis across multiple languages including JavaScript, TypeScript, Python, Ruby, Go, Rust, and more. Use when searching for code patterns based on structure rather than plain text.

ドメイン駆動設計におけるユビキタス言語の確立と適用を専門とするスキル。ドメインエキスパートと開発者が共有する厳密な語彙体系を構築し、コミュニケーションの齟齬を防ぐ。Anchors:• Domain-Driven Design (Eric Evans) / 適用: ユビキタス言語の原則と実践 / 目的: コードとドメインの一貫性確保• Bounded Context / 適用: コンテキスト境界での用語の意味の違いを管理 / 目的: 用語の曖昧さ排除Trigger:Use when establishing domain terminology, creating glossaries, aligning business and technical vocabulary,extracting terms from requirements, defining ubiquitous language for DDD projects,resolving naming conflicts in code, or maintaining domain vocabulary consistency.

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

Electronプロセス間通信（IPC）パターンの設計と実装専門知識。安全で効率的なMain-Rendererプロセス通信、contextBridge、型安全なAPI設計を提供。Anchors:• Electron Security / 適用: contextBridge/preload設計 / 目的: セキュアなIPC実装• Clean Architecture / 適用: Main/Renderer境界設計 / 目的: 責務分離と保守性• Type Safety / 適用: TypeScript型契約 / 目的: IPC通信の型安全性確保Trigger:Use when implementing IPC communication patterns, setting up contextBridge, designing typed IPC handlers, securing renderer-main communication, or structuring bidirectional messaging flows.ipcMain, ipcRenderer, contextBridge, invoke, handle, preload, typed IPC

This skill enables Claude to perform natural language processing and text analysis using the nlp-text-analyzer plugin. It should be used when the user requests analysis of text, including sentiment analysis, keyword extraction, topic modeling, or other NLP tasks. The skill is triggered by requests involving "analyze text", "sentiment analysis", "keyword extraction", "topic modeling", or similar phrases related to text processing. It leverages AI/ML techniques to understand and extract insights from textual data.

Identifies domain modules, ownership boundaries, dependencies, and interfaces using Domain-Driven Design principles. Provides domain maps, bounded contexts, refactor recommendations. Use for "DDD", "domain modeling", "bounded contexts", or "service boundaries".

Provides idiomatic Go programming expertise and best practices. Ensures clean, efficient, and maintainable code following official Go conventions. Specializes in concurrent programming patterns, interface design, error handling strategies, and performance optimization. Masters standard library usage and ecosystem integration. Use when: writing Go code (.go files), designing interfaces and struct types, implementing concurrent patterns (goroutines/channels), handling errors idiomatically, writing table-driven tests, creating Go modules, optimizing performance-critical code, managing dependencies with go.mod, implementing HTTP servers and clients, working with context propagation, or designing package APIs for public libraries.

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). | 適切に設計されたツールを通じてLLMが外部サービスと対話できるようにする高品質MCP（Model Context Protocol）サーバーを作成するためのガイド。Python（FastMCP）またはNode/TypeScript（MCP SDK）で外部APIやサービスを統合するMCPサーバーを構築する際に使用

Generate and edit images using Google's Gemini API (gemini-3-pro-image-preview model). Use when users request (1) Generating images from text prompts, (2) Editing existing images with AI instructions, (3) Creating images with specific styles or templates, (4) Generating multiple variations of images, (5) Creating images with reference images for style consistency, (6) Any image generation task mentioning Gemini, Google AI, or requiring professional image output. Supports aspect ratios (1:1, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9), 7 style templates (3 glass styles, 4 other creative styles), reference images (up to 14), and batch processing.

Use during Phase 2 of spec creation to gather detailed requirements through one-question-at-a-time dialogue - analyzes product context, asks targeted questions, requests visual assets, identifies reusability opportunities, and documents all findings

Tiered testing strategy (UI mock, auth stub, full-stack), fixtures, mocks, and test configuration. Handles test setup, Playwright E2E tests, pytest backend tests, mocking strategies, and CI test configuration. Use when working with tests, test setup, mocking strategies, or CI test configuration, or when user mentions test patterns, auth stub, fixture loaders, Playwright tests, test failures, tiered testing, UI mock, E2E tests, pytest, vitest, or debugging test issues.

Provides comprehensive guidance for managing MCP (Model Context Protocol) servers using the claude mcp CLI. Covers adding servers across scopes (project, local, user), transport types (stdio, sse, http), security best practices, and common patterns. Strongly recommends project scope for team consistency and version control.

Assess skill quality and route to the next refinement operation or conclude that the skill is sufficiently clear. Use when: (1) after any refinement operation completes, (2) at the start of refinement to determine what's actually needed, (3) when uncertain whether further refinement would improve or overwork the text.

Conduct context-driven code reviews focusing on quality, testability, and maintainability. Use when reviewing code, providing feedback, or establishing review practices.

Web research skill for augmenting agent context with current information. Used when outdated information could lead to broken implementations or wasted effort.

When handling form submissions, data mutations, or any action that modifies server-side data. **Version Context**: Next.js 16.0+ uses `useActionState` (replaces deprecated `useFormState`).

META-SKILL ORCHESTRATOR - ALWAYS-ACTIVE. Orchestrates 100% Binora Backend workflows (Django 5.0+DRF 3.14+PostgreSQL multi-tenant) through 6-phase execution (Pre-Analysis, Request Analysis, Workflow Planning, Skill Coordination, Tool Optimization, Quality Assurance). Enforces P0 CRITICAL rules (NO manual tenant_id, service layer mandatory, YOLO comments). Selects optimal model (Sonnet/Haiku). MCP-first strategy (Context7/db/github/sequential-thinking). Target: 3-5x speedup, 95%+ P1 compliance, <500 token overhead.