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「system」の検索結果

7,618 件 ・ 関連度順

概要と使いどころ

Unity 6 ECS/DOTS development guide. Use when working with Entity Component System, data-oriented design, Jobs system, or Burst Compiler. Covers Entities, IComponentData, ISystem, EntityManager, baking, Jobs, and Burst. Based on Unity 6.3 LTS documentation.

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。

IdoCohen560/claude-unity-game-studio222026年7月8日 更新

Use when absorbing ideas, capabilities, workflows, architecture, quality systems, ecosystem extensions, or engineering practices from any reference system into the current project through original, project-native redesign rather than copying.

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。

bovinphang/frontend-craft222026年9月26日 更新

Use when a task needs the judgment of a Computer and Information Systems Manager (IT Manager/Director/CIO-adjacent) — planning IT infrastructure and systems strategy, evaluating a technology vendor or platform decision, allocating an IT budget, or managing IT risk (security, uptime, technical debt) at an organizational level. Broader than the devops-sre or software-engineer roles — this one owns IT as a business function, not a specific engineering discipline.

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。

wonsukchoi/domain-experts212026年10月12日 更新

Write a threat model document. Use when the user says "threat model", "threat modeling", "STRIDE analysis", "attack surface analysis", "security design review", "what are the threats to this system", "adversarial analysis", "identify threats", "security threat assessment", or needs to systematically identify and document threats to a system or feature - even if they don't explicitly say "threat model".

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。

qa-aman/claude-skills202026年10月13日 更新

Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when interacting with gcsfuse: decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size file, stat, and list caches, tune mount flags or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace/HNS, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or bill spikes with gcsfuse metrics. Covers mount semantics, gcsfuse CLI and config files, GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or fully POSIX-compliant shared file systems (Filestore, Managed Lustre).

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。

vaila-multimodaltoolbox/vaila192026年10月8日 更新

Qualitative quality review of game design documents — answers "is this design good, and does it follow best practices?" — across all three GDD axes: systems, flows, and content types. Fans out adversarial lenses (completeness, clarity, pillar alignment, systems-math, fantasy-delivery, feasibility, scope) plus domain lenses that check it against the game-design rules, each prompted to find problems rather than validate; produces a severity-graded verdict and a two-bucket report (apply-ready fixes vs research), handed to /unikit-gd-apply or /unikit-gd-explore in one move. Scope is inferred: a named system, flow, or content type reviews that document; "all" runs a cross-document review. Use when the user wants a critique, quality judgment, or rules check of the design, e.g. "review the combat GDD", "review the onboarding flow". This is the subjective quality pass — for a mechanical consistency check (numbers, terms, IDs, references matching the registry) use /unikit-gd-verify.

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。

NintendaDev/unikit-ai182026年10月10日 更新

Research and ideation partner for GAME DESIGN — think through design ideas before writing them into the GDD; produces a brief, never edits the GDD itself. Use to assess a genre or market for viability, dissect a reference game (mechanics → dynamics → aesthetics), explore how to improve or extend an existing system, flow, or content type, research new mechanics the design lacks, investigate a part of the GDD in code, or develop the research bucket of a /unikit-gd-review report into decided edits. Trigger on "explore how to improve the flow", "ways to improve the combat system", "is this genre saturated", "break down the combat of Hades", "work out the review's open questions". GAME-DESIGN research only — for CODE or technical research use /unikit-explore; to reconstruct a design from code use /unikit-gd-recon; to write a change into the GDD use /unikit-gd-system or /unikit-gd-spec; to apply edits you know use /unikit-gd-apply; to invent a new game use /unikit-gd-brainstorm.

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。

NintendaDev/unikit-ai182026年10月10日 更新

Create reproducible, cross-platform development environments with Flox — a declarative environment manager built on Nix. ALWAYS use this skill when the user needs to: set up a project with system-level dependencies (compilers, databases, native libraries like openssl, libvips, BLAS, LAPACK); configure reproducible toolchains for Python, Node.js, Rust, Go, C/C++, Java, Ruby, Elixir, PHP, or any language; manage environments that must work identically across macOS and Linux; pin exact package versions for a team; run local services (PostgreSQL, Redis, Kafka) alongside development tools; onboard new developers with a single command; or solve 'works on my machine' problems. Especially valuable for AI-assisted and vibe coding — Flox lets agents install tools into a project-scoped environment without sudo, system pollution, or sandbox restrictions, and the resulting environment is committed to the repo so anyone can reproduce it instantly. Use this skill even if the user doesn't mention Flox — if they describe needing reproducible, declarative, cross-platform dev environments with system packages, this is the right tool. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.

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。

tensology/decisionsai172026年10月13日 更新

Create and evolve design systems with design tokens, component architecture, accessibility guidelines, and documentation templates. Ensures consistent, scalable, and accessible UI across products.

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。

manu14357/zskills162026年7月24日 更新

Audita una vista o componente frente al design system en lo que un script no puede comprobar — estados de interacción, los cuatro estados de datos, primitivas nativas frente a componentes reinventados y jerarquía visual. Úsalo cuando la persona pida revisar el cumplimiento del design system o si un componente sigue las guías (p. ej. "¿esta tarjeta sigue nuestro sistema?", "audita la vista de ajustes").

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。

brayandiazc/project-starter-template-es-ai152026年9月23日 更新

Design UI components/design systems, review visual design, check accessibility. Triggers: design system, color palette, font pairing, WCAG check. Data-driven: palettes, fonts, UX guidelines.

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。

ngocsangyem/MeowKit152026年7月28日 更新

Comprehensive guide to designing reliable, scalable data systems covering databases, streaming, and 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。

curiositech/windags-skills142026年10月12日 更新

Creates comprehensive documentation for design systems - token tables, usage guidelines, component examples, and accessibility notes. Use after generating tokens to create developer-friendly docs.

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。

curiositech/windags-skills142026年10月12日 更新

Apply Conway's homomorphism principle to multi-agent system design, recognizing that agent coordination structure predetermines system architecture and capability.

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。

curiositech/windags-skills142026年10月12日 更新

Build daemon/background processes that start on boot, run continuously, and manage their own lifecycle. Covers macOS launchd (plist files, agents vs daemons), Linux systemd (unit files), Windows services, process supervision, logging, health checks, graceful shutdown, auto-restart, and AI-powered daemons that manage LLM API connections and rate limits. Activate on: "daemon", "background process", "launchd", "systemd", "service file", "plist", "launch agent", "launch daemon", "auto-start", "always running", "process supervisor", "pm2", "background service", "boot service", "AI daemon", "long-running process". NOT for: container orchestration (use devops-automator), cron jobs that run and exit (use task-scheduler), web server deployment (use backend-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。

curiositech/windags-skills142026年10月12日 更新

Integration of BDI agent architecture with soft systems methodology for complex organizational problem-solving

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。

curiositech/windags-skills142026年10月12日 更新

Choose multi-agent architectures using environment-first analysis, coordination pressure, commitment tuning, and knowledge levels. Use for autonomy design, protocol choice, and coordination failures. NOT for single-agent planning, centralized schedulers, or prompt-only swarms.

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。

curiositech/windags-skills142026年10月12日 更新

An infographic skill for AI agents — works inside Claude Code, Codex, Hermes, OpenClaw, Cursor, and any agent host that loads skills. Create professional infographics as self-contained HTML files with PNG exports. Use when the user asks to create, design, generate, build, or make an infographic, data visualization, visual explainer, chart poster, cheatsheet, or pocket guide. Trigger phrases include "make this visual", "turn this into a graphic", "visualize this data", "infographic for X", "cheatsheet for X", or when the user provides structured data (tokenomics allocations, ecosystem/partner lists, timelines, comparisons, step-by-step processes) AND asks for a visual output. Covers tokenomics, ecosystem overviews, game overviews, cheatsheets, airdrop guides, comparisons, and process flows. Do NOT trigger for plain text answers, markdown tables, bulleted summaries, questions asking for advice or explanations about a topic (even when the topic is tokenomics, ecosystem, vesting, etc.), inline chat diagrams, or data processing with no visual output requested. The signal is "asks for a visual", not "mentions a keyword".

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。

aizzaku/aiz-infographic142026年5月25日 更新

Expert-level distributed systems theory covering consistency models, consensus algorithms, fault tolerance, replication, distributed transactions, and the CAP theorem.

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。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level spacecraft design covering mission analysis, subsystem design, power and thermal management, attitude control, communications, and systems 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。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level power systems covering power generation, transmission, distribution, power flow analysis, fault analysis, protection, and power electronics.

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。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level database systems theory covering relational model, query processing and optimization, transaction management, concurrency control, recovery, and NoSQL 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。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level control systems engineering covering feedback control, PID design, root locus, frequency domain methods, state-space design, and digital control.

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。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新

Expert-level embedded systems covering microcontrollers, RTOS, peripheral interfaces, low-power design, bare-metal programming, and embedded Linux.

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。

luokai0/ai-agent-skills-by-luo-kai122026年5月6日 更新