「system」の検索結果

Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3 Storage Lens tables via Athena SQL. Applies when counting objects, finding recent uploads or deletions, identifying who wrote to a prefix, breaking down storage classes, finding objects by tag, searching annotation content, analyzing storage lens metrics, or enabling S3 Metadata tracking. Prefers system tables over raw S3 APIs (list-objects-v2, head-object) at scale. Trigger phrases: bucket activity, object count, who uploaded, track deletions, storage class breakdown, find by tag, search annotations, storage lens metrics, audit bucket changes.

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Implement Apollo.io reference architecture. Use when designing Apollo integrations, establishing patterns, or building production-grade sales intelligence systems. Trigger with phrases like "apollo architecture", "apollo system design", "apollo integration patterns", "apollo best practices architecture".

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Production-grade architecture patterns for Apify-powered applications. Use when designing scraping infrastructure, building multi-Actor pipelines, or integrating Apify into a larger system architecture. Trigger with "apify architecture", "apify best practices", "apify project structure", "scraping architecture", "apify system design".

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。

Skillshare frontend design system for the React dashboard (ui/) and Docusaurus website (website/). Use this skill whenever you: build or modify a dashboard page or component in ui/src/, style or layout website pages or custom CSS in website/, create new React components for the dashboard, add pages to the dashboard, fix visual bugs in either frontend, or need to know which design tokens, ss-* classes, components, or patterns to use. Covers the two dashboard styles (Clean / Playful) in light and dark, design tokens, the ss-* class system, component API, page structure, accessibility, keyboard shortcuts, and anti-patterns. Even if the user just says "fix the styling" or "add a card", use this skill to ensure consistency.

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。

Rust systems programming patterns including ownership, traits, async runtime, error handling, and unsafe guidelines

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Grida AI agent system work: `@grida/daemon` (DaemonServer, loopback HTTP perimeter, files/workspaces, secrets store, daemon discovery) and `@grida/agent` (the agent tenant: sessions, providers/BYOK, runtime/tool execution, skills discovery, prompts, tiers, sandbox hosts). Use for `packages/grida-daemon/**`, `packages/grida-ai-agent/**`, desktop sidecar protocol changes, agent chat transport, and bugs in agent state or streams. For pure Electron window, preload, menu, deep-link, or CDP work, use `desktop`.

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Rebuilds an app's design system for a clone: colour roles, type scale, spacing, radius, shadows and every component with its states, as design tokens plus component specs, with original assets instead of the target's logos, icons, illustrations or licensed fonts. Includes a WCAG contrast checker. Use when the user says "match the design", "rebuild the design system", "get the colours and fonts", "make it look like X", "design tokens for my clone", or after /replica-architect.

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 architecture documentation using C4 model Mermaid diagrams. Use when asked to create architecture diagrams, document system architecture, visualize software structure, create C4 diagrams, or generate context/container/component/deployment diagrams. Triggers include "architecture diagram", "C4 diagram", "system context", "container diagram", "component diagram", "deployment diagram", "document architecture", "visualize architecture".

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Comprehensive guide for creating software diagrams using Mermaid syntax. Use when users need to create, visualize, or document software through diagrams including class diagrams (domain modeling, object-oriented design), sequence diagrams (application flows, API interactions, code execution), flowcharts (processes, algorithms, user journeys), entity relationship diagrams (database schemas), C4 architecture diagrams (system context, containers, components), state diagrams, git graphs, pie charts, gantt charts, or any other diagram type. Triggers include requests to "diagram", "visualize", "model", "map out", "show the flow", or when explaining system architecture, database design, code structure, or user/application flows.

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Build and iterate playable Three.js game systems: starter scaffold, architecture, design briefs, core loops, level and encounter design, entities, input, camera, collision and physics, scoring, objectives, and game feel. Use for first playable slices, new Vite/TypeScript/Three.js setups, level/arena/track/wave/hole/puzzle design, combat encounters, difficulty tuning, and juice.

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Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

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Select, pair, and implement typefaces for web projects. Use when the user mentions "font pairing", "which typeface", "line height", "responsive typography", "web font loading", "type hierarchy", "variable fonts", "FOUT/FOIT", "typographic scale", or "the text is hard to read". Also trigger when choosing between system fonts and web fonts, optimizing font-loading performance, or designing readable long-form content. Covers readability evaluation, CSS implementation, and performance optimization. For overall UI design systems, see refactoring-ui. For dramatic typographic experiences, see top-design.

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Guided journey from a working-but-untested vibe-coded prototype to a production-ready product with tests, clean structure, a business-rules boundary, and resilience at scale. Orchestrates nine skills phase by phase - working-with-legacy-code, clean-code, refactoring-patterns, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, system-design, ddia-systems - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, IMPROVE-CODE-QUALITY-PLAN.md) so the journey resumes across sessions. Use when the user wants to harden an AI-generated prototype, add tests before refactoring, make code safe to change, or says 'this works on my machine but I am scared to touch it'. For an aged codebase, remove-technical-debt; for greenfield structure, design-code-architecture; for a product and UX pass, improve-app; to optimize speed and structure, architecture-optimization. For one framework in isolation, invoke that skill directly.

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。

Guided journey from a working codebase grown slow and tangled to one measurably fast, cleanly bounded, and readable. Orchestrates eight skills phase by phase - working-with-legacy-code, clean-architecture, software-design-philosophy, refactoring-patterns, system-design, ddia-systems, release-it, pragmatic-programmer - every phase carries its method inline so it runs standalone, asking the user questions at every decision point and recording results in the project docs/ folder (PERFORMANCE.md, ARCHITECTURE.md, ARCHITECTURE-OPTIMIZATION-PLAN.md) so the journey resumes across sessions. Use when the user wants to make an app faster, untangle drifted boundaries, fix slow endpoints and queries, or says 'it works but it is slow and getting worse'. For an untested prototype, improve-code-quality; for an aged codebase you fear to touch, remove-technical-debt; for greenfield structure, design-code-architecture; for marketing-site page speed, improve-website. For one framework in isolation, invoke that skill directly.

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Guided journey from an app idea to a deliberate architecture: boundaries, domain model, data decisions, and resilience, making only the expensive-to-reverse decisions and deferring the rest. Orchestrates eight skills phase by phase - clean-architecture, domain-driven-design, system-design, ddia-systems, software-design-philosophy, release-it, pragmatic-programmer, 37signals-way - asking the user questions at every decision point and recording results in the project docs/ folder (ARCHITECTURE.md, DESIGN-CODE-ARCHITECTURE-PLAN.md) so the journey resumes across sessions. Use when the user wants to design a new app's architecture, choose boundaries and a domain model, decide monolith versus microservices, or says 'how should I structure this app'. If a codebase already exists, use remove-technical-debt (aged), improve-code-quality (fresh prototype), or architecture-optimization (slow but working); if unvalidated, run create-business or create-app first. For one framework in isolation, invoke that skill directly.

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 motivation systems using Autonomy, Mastery, and Purpose (AMP) for products and teams. Use when the user mentions "intrinsic motivation", "gamification isnt working", "rewards arent working", "autonomy", "mastery", "purpose-driven", "my team is disengaged", or "how do I motivate people". Also trigger when designing onboarding progression, fixing broken gamification, or building team structures that sustain high performance. Covers why carrot-and-stick fails and how to build progress systems. For habit-forming product loops, see hooked-ux. For retention behavior design, see improve-retention.

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Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.

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Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.

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Identifies what could go wrong in a system before it is built or changed — the assets worth attacking, the entry points, the trust boundaries, and the controls that actually address the realistic threats. Use this when designing a feature or system, when a change touches authentication, data handling, payments, or external input, before a security review, or when deciding which security work is worth doing at all.

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Designs system structure and makes architectural decisions defensible — boundaries, coupling, trade-offs, and recording why. Use this to design a new system or major component, choose between architectural options, review an existing design, decide where a boundary belongs, or document an architectural decision so it survives the people who made it.

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Protects data itself rather than the systems around it — classifying what you hold, encrypting in transit and at rest and understanding what each actually defends against, managing keys and their rotation, handling secrets in applications and pipelines, minimizing and de-identifying, and deleting on purpose. Use this to design data protection for a system, assess an encryption claim, set up key or secret management, or work out what a stolen backup would actually expose.

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Builds and maintains the design system a product is assembled from — tokens for color, type, spacing and elevation, component contracts, and the rules that keep them coherent as the product grows. Use this when starting a new interface, when screens have drifted apart visually, when the same component exists three times in slightly different forms, or when a token or component needs adding without breaking what exists.

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Runs voice and meeting infrastructure — phone systems and numbers, emergency calling obligations, conference rooms and their AV, call recording and its retention consequences, and the porting that makes provider changes go badly. Use this to replace a phone system, fix rooms nobody can start a meeting in, meet emergency-calling requirements, port numbers without losing service, or work out why voice quality degrades only sometimes.

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Handles a dispute from the first sign of it — recognizing when preservation obligations attach, issuing and scoping a legal hold, suspending automatic deletion across every system that holds relevant material, preserving privilege, managing outside counsel and cost, and evaluating settlement against the real cost of continuing. Use this to respond to a claim or demand letter, issue a hold, work out which systems the hold has to reach, or decide whether to fight.

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。