「engine」の検索結果

Expert en ingénierie du contexte IA (compression de prompts, chunking, gestion tokens, optimisation fenêtre)

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 en direction artistique IA (Midjourney, DALL-E, Stable Diffusion, prompt engineering, cohérence de style)

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。

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.

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。

Transforms user prompts into optimized prompts using frameworks (RTF, RISEN, Chain of Thought, RODES, Chain of Density, RACE, RISE, STAR, SOAP, CLEAR, GROW)

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。

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

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 choosing an animation engine, defining motion tokens, adding scroll effects or micro-interactions, or auditing motion for accessibility and performance. Covers engine selection (GSAP, Motion.dev, Anime.js, React-Spring, Three.js, CSS Native), DTCG motion tokens, and the anti-slop/a11y quality gate.

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。

Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.

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。

BDB Engineering Godmode, enforcing strict Domain-Driven Design, TypeScript strictness, and Clean Architecture. Use when implementing backend/fullstack features or running the systematic 5-step debugging triage.

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。

Frontend design blueprints with craftsmanship scoring, self-critique loops, and engineering handoff. Aesthetic intelligence against AI homogeneity. Use for: UI/UX design specs, design system creation, visual direction exploration, component design review, design-to-engineering handoff.

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。

Multi-agent SWE team built on the Workshop model. Full-stack vertical workers, meeting room with @mention notification, private pipes, shared task board. Git worktree isolation, Leader-driven coordination. Mixed Codex/Claude Code engine. Use when a task needs engineering depth beyond a single agent. NOT for simple task parallelism (use agent-task-orchestration) or design discussions (use agent-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。

ソフトウェア・エンジニアリングのための倫理集。開発時に必ず意識するものです。

Responsive design engineering: production-level container queries, fluid type, 320 to 4K. Use when implementing, reviewing or testing responsive design engineering for React, Vite, Next.js or Perfect_AI projects.

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。

Color selection engine: production-level product intent -> palette -> contrast -> tokens. Use when implementing, reviewing or testing color selection engine for React, Vite, Next.js or Perfect_AI projects.

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。

GitHub engineering: production-level branches, PR review, changelog, licenses. Use when implementing, reviewing or testing github engineering for React, Vite, Next.js or Perfect_AI projects.

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: implement a scoped ticket, fix a bug, add tests, prepare a PR-ready code change, or reuse a standard builder workflow across software engineer agents.

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。

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

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 effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when: prompt engineering, system prompt, few-shot, chain of thought, prompt 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。

Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug 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。

When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," or "free resource." This skill bridges engineering and marketing — useful for founders and technical marketers.

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。

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

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。

You know AI wrappers get a bad rap, but the good ones solve real problems. You build products where AI is the engine, not the gimmick. You understand prompt engineering is product development. You balance costs with user experience. You create AI products people actually pay for and use daily.

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。

Capture The Flag challenge solving — reverse engineering, steganography, forensics, crypto, web exploitation, binary exploitation, OSINT. Pattern recipes for fast triage and direct exploitation.

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。

Search the public web and crawl URLs via the Unique AI Platform's `unique-cli web-search` command, with automatic per-turn citation tracking so cited web facts render as clickable external reference chips and `<sup>N</sup>` footnotes on the Unique platform. ALWAYS use this skill when the user asks to search the public web, research a topic online, look up news/articles/regulations, fetch the contents of one or more URLs, or perform any "two-phase" web research (search → review snippets → crawl selected URLs for full content). Routes through the Unique AI Platform's `/web-search-api` endpoints, so the engine (Google, Brave, Tavily, Jina, Firecrawl, …) and crawler are resolved server-side from the current environment — you never need to manage engine API keys yourself. Use this instead of fabricating answers from training data whenever fresh / source-cited information is needed. Do NOT use this skill for the internal knowledge base (`unique-cli search`) or for arbitrary tool execution (`unique-cli mcp`).

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。

The default code-driven browser path for interactive browsing work: drives any browser from code with token-efficient a11y snapshots (57% smaller via compactSnapshot), ref-based clicks, coordinate control (CUA), viewport pinning, CAPTCHA solving (reCAPTCHA, Turnstile, hCaptcha, slider, OCR), Chrome MV3 APIs (tabs/bookmarks/history/downloads/topSites), network snoop (read API JSON instead of DOM), flight-recorder trace (jsonl + HAR + screenshots), OOPIF-aware snapshots, dialog policy, human handoff for login/OTP, device emulation, request routes, stealth via CloakBrowser as the default owned engine with zero exposed CDP ports, and an attached engine that drives the user's own signed-in browser through BrowserSkill (connectBrowserSkill, bskSnapshot, one-click onboarding via bskOnboard). MUST USE for interactive browser work: scraping, blocked/WAF/JS-rendered pages, logins, the user's logged-in sites and open tabs, extension popups, form filling, screenshots, web QA, CAPTCHAs. The ulw-research browsing lane runs on ultimate-browsing, not this skill.

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。