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概要と使いどころ
Transform vague inputs into precision-optimized AI prompts for Claude, ChatGPT, Gemini, or other LLMs. Use when user mentions "optimize prompt", "improve prompt", "lyra", "prompt engineering", or needs help crafting effective AI prompts.
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。
Manages cloud infrastructure through natural language conversations with Pulumi Neo, an AI agent for platform engineers. Enables infrastructure analysis, resource provisioning, stack deployment, and configuration management via conversational AI. Use when creating Neo tasks, requesting infrastructure analysis, automating cloud deployments, managing infrastructure as code (IaC), provisioning AWS/Azure/GCP resources, managing infrastructure through natural language prompts, reviewing PRs with Neo, handling Neo approval workflows, or checking Neo task status and events. Also use when the user mentions "Pulumi Neo", "Neo task", "Neo agent", or wants AI-assisted infrastructure management.
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。
Generates Spring Boot 3.x configurations, creates REST controllers, implements Spring Security 6 authentication flows, sets up Spring Data JPA repositories, and configures reactive WebFlux endpoints. Use when building Spring Boot 3.x applications, microservices, or reactive Java applications; invoke for Spring Data JPA, Spring Security 6, WebFlux, Spring Cloud integration, Java REST API design, or Microservices Java 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。
Writes, reviews, and debugs idiomatic Rust code with memory safety and zero-cost abstractions. Implements ownership patterns, manages lifetimes, designs trait hierarchies, builds async applications with tokio, and structures error handling with Result/Option. Use when building Rust applications, solving ownership or borrowing issues, designing trait-based APIs, implementing async/await concurrency, creating FFI bindings, or optimizing for performance and memory safety. Invoke for Rust, Cargo, ownership, borrowing, lifetimes, async Rust, tokio, zero-cost abstractions, memory safety, systems programming.
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。
Family coordination engine. Use this skill whenever the user mentions meals, meal planning, groceries, weekly schedule, family logistics, kid activities, custody schedule, co-parent coordination, family dashboard, weekly briefing, weekly prep, "what's for dinner", school events, pickup/dropoff, babysitter, pediatric nutrition, grocery list, grocery cart, "load the cart", "load the carts", "bargain hunt", "find the deals", "compare prices", "price check", "smart split", "save money on groceries", family calendar review, or anything involving coordinating schedules and meals for a family. Also trigger when the user says "parent helper", "family mode", "week ahead", or "plan the week". Trigger on local event queries: "what's going on", "things to do", "events this weekend", "anything happening", "stuff to do", "what can we do with the kids", "family stuff this weekend". This skill is the central hub — if it touches the family schedule, the family's food, or local family-friendly events, it belongs here.
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。
Perform a dual-lens critical review of the specification and plan from both product strategy and engineering risk perspectives 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。
General electrical engineering support for hardware design and review. Load the canonical Circuit Weaver skill from `skills/ee/SKILL.md`.
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。
Electrical and electronic engineering reference — circuit analysis, component selection, power supply design, signal integrity, RF, thermal, EMC, and test & measurement. Use for design questions, calculations, component vetting, and first-principles analysis. Do not orchestrate a complete new board from requirements; use circuit-weaver for that end-to-end 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。
Use when the user wants to systematically fix AI code slop — duplicated logic, over-engineering, silent error swallowing, convention drift, cargo-cult patterns, and other LLM-introduced architectural decay — over a specified duration
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。
Install, configure, and work with Turso DB — an in-process SQLite-compatible relational database engine written in Rust. Use when the user needs to (1) install Turso DB, (2) create or query databases with the tursodb CLI shell, (3) use Turso from JavaScript/Node.js via @tursodatabase/database, (4) work with vector search or embeddings in Turso, (5) set up full-text search with FTS indexes, (6) configure transactions including MVCC concurrent transactions, (7) enable encryption at rest, or (8) use Change Data Capture (CDC) for audit logging.
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。
Installs and configures reverse engineering tools including radare2, Ghidra, GDB, QEMU, Frida, and cross-compilation toolchains for ARM64, ARMv7, x86_64, and MIPS. Use when a tool command fails, a required tool is missing, or you need to set up a fresh analysis environment.
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。
Analyzes ELF binaries, executables, and firmware images to understand behavior without source code; coordinates sub-skills binary-re:triage, binary-re:static-analysis, binary-re:dynamic-analysis, binary-re:synthesis, and binary-re:tool-setup. Use when working with a binary, executable, or ELF file; asked to reverse engineer, disassemble, decompile, or figure out what something does; targeting ARM64, ARMv7, x86_64, or MIPS; or analyzing Python bytecode (.pyc, marshal). For Python bytecode analysis, see docs/python-bytecode-re.md.
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 then build — chains architecture review into implementation. Accepts any spec format (ticket, PRD, engineering spec, feature description, screenshot) and autonomously reviews the design, resolves gaps, then implements with tests and a PR.
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。
Audit a government or public services system for compliance, fraud risk, and security — chains benefits processing review, fraud detection analysis, regulatory compliance check (ADA, Section 508, FISMA, Privacy Act), and PII-focused security audit. Use for benefits platforms, eligibility engines, enrollment portals, or inter-agency data systems.
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。
Audit corporate tax compliance systems across jurisdictions. Analyzes tax engine configuration (Avalara, Vertex, ONESOURCE), nexus determination and Wayfair economic nexus tracking, sales/use tax calculation accuracy, federal and state income tax compliance (book-to-tax adjustments, NOL.
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。
Dynamic pricing engine for short-term rentals (Airbnb, VRBO, Booking.com, Direct) — sets nightly rates based on a comp set (40+ filters: bedrooms, bathrooms, amenities, location radius, rating tier), seasonality patterns (weekly + monthly + annual cycles per market).
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 ASC 606 / IFRS 15 revenue recognition engine for SaaS — the five-step model (identify contract, identify performance obligations, determine transaction price, allocate to performance obligations, recognize as POs are satisfied) applied to subscription contracts.
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。
Audit a quoting or estimation system -- analyze labor hour estimation accuracy, material take-off completeness, pricing rule engines, markup and margin optimization, good-better-best tiered pricing, and quote-to-close win rates.
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。
Audit financial reconciliation workflows -- evaluate automated transaction matching engines, intercompany balance reconciliation, suspense and clearing account health, variance root-cause investigation, and close calendar integration.
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。
Audit e-commerce and retail product return systems for return rate reduction strategies, reverse logistics efficiency, refurbishment routing, fraud detection in returns, and return reason analytics. Use when reviewing order management systems, RMA workflows, warehouse return processing, disposition engines, or retail loss prevention tools.
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。
Autonomous SEO + AI-search optimization agent for 2026. Audits and fixes technical SEO, on-page metadata, structured data, Core Web Vitals (LCP/INP/CLS), llms.txt, Generative Engine Optimization (GEO) for ChatGPT/Perplexity/AI Overviews, E-E-A-T author signals.
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。
Audit a real estate analytics platform -- evaluate comparable sales and rental engines, automated valuation models (AVM), demographic and economic indicator pipelines, submarket scoring, gentrification detection, price forecasting accuracy, market cycle analysis, and risk modeling.
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。
Audit laboratory automation systems -- LIMS architecture, instrument connectivity (SiLA 2, OPC-UA, serial drivers), sample tracking and chain of custody, protocol workflow engines, data acquisition pipelines, and regulatory compliance (21 CFR Part 11 electronic records/signatures.
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 a production-grade OEE (Overall Equipment Effectiveness) measurement pipeline for a manufacturing line — data ingestion from MQTT/OPC-UA/Modbus/CSV, A×P×Q calculation engine, Six Big Losses categorizer, MTBF/MTTR/TEEP metrics, Grafana or Streamlit dashboard.
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。