「systems」の検索結果

Use this skill whenever the user wants to use AI agents to work with Penpot design files via the Penpot MCP Server. Triggers include: using Penpot through an AI agent, design files, design systems, design tokens, Penpot MCP, design-to-code, generating UI from design, auditing a design system, creating components/variants, renaming layers, exporting assets from Penpot, adding flows, interactions, animations, overlays, or prototyping in Penpot, or prompting an AI agent to read/modify a Penpot file. Also triggers when the user wants to set up Penpot MCP, connect any MCP-compatible AI agent or IDE to Penpot, or produce production-ready HTML/CSS/React from a Penpot design. Use this skill for Penpot-agent workflows — design, code, audit, prototyping, or setup.

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 the hyalo CLI instead of read/edit/grep/write when working with markdown (.md) files that have YAML frontmatter. This skill MUST be consulted whenever pi is working with markdown documentation directories, knowledgebases, wikis, notes, Obsidian-compatible collections, Zettelkasten systems, iteration plans, or any collection of .md files with frontmatter. Trigger this skill when: searching or filtering markdown files by content, tags, or properties; reading or modifying YAML frontmatter; managing tags or metadata across documents; toggling task checkboxes in markdown; getting an overview of a documentation directory; querying document properties or status fields; bulk-updating metadata across many markdown files; or when you find yourself repeatedly using read/edit/grep/write on .md files. Even if the user does not mention "hyalo" by name, use this skill whenever the task involves structured markdown documents with frontmatter. For pi sessions, ALWAYS use `--format text` for compact, LLM-friendly output.

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 designing, optimizing, testing, or deploying robust prompt systems for AI agents. This skill provides frameworks for structured prompt engineering, meta-prompting, and automated optimization workflows.

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。

Bash/Linux terminal patterns. Critical commands, piping, error handling, scripting. Use when working on macOS or Linux 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。

Game audio principles. Sound design, music integration, adaptive audio 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。

Use when implementing or managing persistent, hierarchical memory systems for AI agents. Covers cross-session state, fact supersession, and self-managed memory tools to enable long-term recall and adaptive agent behavior.

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 building self-correcting retrieval systems for AI agents. Keywords: RAG, retrieval, Corrective RAG, Self-RAG, query decomposition, reranking, hallucination, grounding.

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 authentication and authorization with Better Auth - a framework-agnostic TypeScript authentication framework. Features include email/password authentication with verification, OAuth providers (Google, GitHub, Discord, etc.), two-factor authentication (TOTP, SMS), passkeys/WebAuthn support, session management, role-based access control (RBAC), rate limiting, and database adapters. Use when adding authentication to applications, implementing OAuth flows, setting up 2FA/MFA, managing user sessions, configuring authorization rules, or building secure authentication systems for web applications.

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。

Create beautiful, accessible user interfaces with shadcn/ui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs. Use when building user interfaces, implementing design systems, creating responsive layouts, adding accessible components (dialogs, dropdowns, forms, tables), customizing themes and colors, implementing dark mode, generating visual designs and posters, or establishing consistent styling patterns across applications.

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。

Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.

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。

Expert prompt engineer specializing in designing, optimizing, and managing prompts for large language models. Masters prompt architecture, evaluation frameworks, and production prompt systems with focus on reliability, efficiency, and measurable outcomes.

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。

Expert in designing, orchestrating, and managing multi-agent systems (MAS). Specializes in agent collaboration patterns, hierarchical structures, and swarm intelligence. Use when building agent teams, designing agent communication, or orchestrating autonomous workflows.

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。

Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.

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。

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm

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。

Expert error coordinator specializing in distributed error handling, failure recovery, and system resilience. Masters error correlation, cascade prevention, and automated recovery strategies across multi-agent systems with focus on minimizing impact and learning from failures.

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。

This skill should be used when building AI agents using prompt-native architecture where features are defined in prompts, not code. Use it when creating autonomous agents, designing MCP servers, implementing self-modifying systems, or adopting the "trust the agent's intelligence" philosophy.

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 asks to design multi-agent systems, create agent architectures, define agent communication patterns, or build autonomous agent workflows.

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 whenever the user asks for an HTML-first visual design deliverable or design judgment: interactive prototype, slide deck, motion demo, infographic, dashboard, landing page, whitepaper, changelog, business card, social cover, brand system, design critique, multi-variant exploration, or export to MP4, GIF, PPTX, PDF, or SVG. It is optimized to make AI agents do the routing, template selection, verification, and export prep so humans spend less time prompt-engineering. Do not use for production web apps, SEO sites, backend systems, or pure copy edits.

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。

Agent-native design engine that makes AI do more useful work: route the prompt, fork a template, weave IFQ ambient craft, verify the artifact, and only install export tooling when requested. One prompt -> shippable HTML, with optional MP4 / GIF / PPTX / PDF / SVG. Triggers include prototype, hi-fi mockup, slide deck, motion demo, infographic, dashboard, whitepaper, changelog, business card, social cover, brand from scratch, design critique, mp4/gif export, 60fps, keynote, PPTX, A-vs-B benchmark. Do not use for production web apps, SEO-critical sites, backend systems, or pure copy edits.

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。

MATLAB R2026a workflow for control systems, system identification, robust control, MPC, Simulink Control Design, parameter tuning, constrained optimization, and numerical validation. Use whenever the user asks for controllers, transfer functions, state-space models, tuning, identification, optimal control, or solver-based engineering.

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。

AI governance audit using ISO 42001 standard. Ensures AI systems are developed and deployed responsibly with risk management, ethics, security, transparency, and compliance best practices.

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。

Founder Brand And Thought Leadership Specialist. Use to define founder IP territory, create content systems for X and LinkedIn, and turn founder experience into audience, distribution, and credibility.

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 a pull request or contribution deeply, explain it tutorial-style for a maintainer, and produce a polished report artifact such as HTML or Markdown. Use when asked to analyze a PR, explain a contributor's design decisions, compare it with similar systems, or prepare a merge recommendation.

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。

Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.

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。