3,075 件 ・ 関連度順
概要と使いどころ
Framework for competitive landscape analysis across any industry. Use when creating competitor analysis, market positioning assessments, investment memos, strategic reviews, or any analysis requiring systematic evaluation of competitive dynamics. Triggers include requests for competitive landscape decks, peer comparisons, market structure analysis, strategic positioning assessments, and investment recommendations.
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 automate capture of marketing screenshots for a SwiftUI iOS app across multiple locales, devices, or appearances. Covers full-screen shots, isolated element renders (carousel cards, widgets), and reproducible output naming. Triggers on marketing screenshots, locale screenshots, widget renders, App Store assets, fastlane-alternative, simctl screenshots.
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。
Semi-automated fact-checking, source credibility evaluation, misinformation detection, prebunking, and evidence-ledger based claim verification. Use when a user asks to verify a claim, article, social post, screenshot, URL, quote, data point, compare sources, detect manipulation, evaluate source reliability, or generate an HTML fact-check card/share-safe correction. Supports text, URLs, screenshots/images, two-source comparison, and topic-level prebunking in Bulgarian, English, Russian, EU policy, health, science, and geopolitical contexts. Trigger phrases: "is this true?", "is this fake?", "fact check this", "compare these sources", "проверка на факти", "истина ли е", "дезинформация ли е", "сравни тези източници".
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 a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.
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 Grok 4.5 as the required external design advisor when a task needs UI critique, UX critique, component-choice review, interaction-flow review, design imagery markdown, art direction, visual hierarchy judgment, design-system fit, color/type/layout suggestions, HTML mockups, SVG icons, handwritten SVG wordmarks, or file-based feedback on existing UI. Trigger on requests like "design a page", "generate design imagery", "give design advice", "optimize this UI", "improve UX", "optimize user flow", "review interaction", "check usability", "reduce friction", "choose the right component", "review this design", "create an icon", "suggest colors", "UI mockup", "visual direction", "lettering", "wordmark", "handwritten logo", or when another agent needs a second opinion on visual or interaction quality.
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。
Miro presents itself as the AI-powered visual workspace through a confident, almost playful brand voice — anchored by its signature canary yellow ({colors.brand-yellow}) wordmark over white canvas, broken open by colorful pastel feature tints (rose, teal, coral, orange, mint) that echo the actual sticky-note color palette used on the live whiteboard. Black-pill primary buttons dominate marketing, real Miro-board mockups serve as feature illustrations, and a 4-tier pricing grid leads into a dense comparison table. Roobert PRO carries display headlines; the system supports homepage, pricing, AI Workflows product page, agile vertical, and customer stories surfaces.
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。
Connects Claude Code, Codex, Cursor, and other MCP hosts to Writingmate for model discovery, text comparison, image generation, and video generation with Seedance, Sora, Veo, Kling, PixVerse, and other available models.
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。
Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.
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。
Mintlify presents documentation infrastructure with a dual-mode aesthetic — atmospheric sky-gradient marketing heroes (cloud illustration backdrops, soft cream-to-blue washes) paired with dense developer-grade documentation surfaces. The system uses Inter for UI prose, Geist Mono for code, and a signature Mintlify green ({colors.brand-green}) reserved for accent CTAs and active states. Black-pill primary buttons dominate marketing, white-on-dark inversions appear on dark hero bands, and a 3-column documentation layout (sidebar / prose / TOC) anchors the developer experience. Coverage spans homepage, startups program, pricing comparison, and the live tabs documentation page.
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 working with Aws Batch — aWS Batch compute environment management, job queue analysis, scheduling policy review, and array job monitoring. Covers compute resource utilization, job status tracking, failure investigation, Fargate vs EC2 comparison, and queue priority analysis.
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 sales-ready competitive battlecards comparing your product against a specific competitor — positioning, feature comparison, objection handling, and win/loss patterns. Use when preparing sales teams, creating competitive materials, or responding to 'why not competitor X?'
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。
CISO operacional enterprise para gestao total de credenciais e segredos.
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。
Enforces baseline comparisons, cross-validation, interpretation, and leakage prevention for ML pipelines
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。
Inspect factory health, stale work, CI, security advisories, and recent run evidence without implementing fixes.
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。
Scheduled health sweep that closes the factory loop - reads CI failures, recent commits, dependency and security advisories, and live queue labels, then files issues and writes an immutable run record. Use for the nightly or weekly monitor routine.
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。
Acts as a director and previs supervisor for film, video, and AI filmmaking. Turns scripts, prose, briefs, or existing image and video assets into production deliverables — subtext breakdown, beat sheet, director's book, blocking and staging, shot list with coverage, keyframe and storyboard prompts, image-to-video motion prompts, sound and dialogue plans, edit timelines, continuity bibles, and QC repair notes. Carries genre playbooks, a controlled prompt lexicon, a coded failure-diagnosis manual, and capability-first adapters for current video and image models. Optionally applies one named director's style lens — Spielberg, Hitchcock, Kubrick, Kurosawa, Scorsese, Fellini, Bergman, Tarkovsky, Wong Kar-wai, Nolan, Villeneuve, Fincher, Refn, Bi Gan, Zhang Yimou, Hou Hsiao-hsien, Park Chan-wook, Malick, Michael Mann, Coen Brothers. Use for shot planning, blocking, staging, camera movement, visual continuity, storyboard and keyframe design, prompt repair, "in the style of X" direction, and any AI video 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 is transitioning from a completed retro into a weekly plan, choosing weekly outcomes, scheduling a full ISO week, or asking for "план на неделю", "weekly planning", priorities, capacity, or 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。
Use when a completed department retro should become accepted outcomes and a full living ISO-week plan, or the user asks "планирование", "план недели", or "что делаем на следующей неделе".
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 between engines or models for an agent pipeline and the answer must come from measurement on your own data, not from marketing pages: speech recognition for meeting recordings, the model that turns a transcript into notes, the critic model that checks it. Runs every variant in an isolated container, measures time, cost per hour of input (USD and RUB, with price source and date) and quality (WER/CER and course terms for ASR; code checks plus a judge of a different model for LLM steps), writes results.json/csv and one static analytics page. Triggers on "бенчмарк", "сравни движки", "сколько стоит час записи", "какую модель взять для пайплайна", "benchmark the pipeline", "compare ASR engines".
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。
Готовит многомерный разбор конкурентов — feature-матрица, SWOT с cross-strategy, 5 сил Портера, сравнение ценообразования, позиционирование, прогноз стратегических ходов и три уровня дифференциации (догнать / отстроиться / создать новое). Адаптируется под цель (продуктовый дизайн / fundraising / стратегия / годовой обзор). User-invoked only — do NOT auto-trigger. Triggers on /pm-competitive, "конкурентный анализ", "разбор конкурентов", "five forces", "SWOT", "competitive analysis", "competitor comparison", "feature matrix vs competitors".
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 is closing an ISO week, reviewing planned outcomes against evidence, interviewing work Areas, resolving unfinished commitments, or asking for "ретро", "weekly retro", "week review", or lessons from the week.
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。
TanStack AI (alpha) provider-agnostic type-safe chat with streaming for OpenAI, Anthropic, Gemini, Ollama. Use for chat APIs, React/Solid frontends with useChat/ChatClient, isomorphic tools, tool approval flows, agent loops, multimodal inputs, or troubleshooting streaming and tool definitions.
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。
Analyze a software repository at the latest remote main commit and turn its implemented architecture into a citation-backed interactive isometric system map with a legend, selectable infrastructure buildings, dependency and payload flows, and plain-language learner explanations. For eligible public GitHub repositories, also contribute the verified map to tamdogood/CodeTerrain with a pull request. Use when a user provides a repository URL or asks to visualize, explore, learn, explain, or map a repo's architecture, infrastructure, runtime control flow, data flow, services, queues, stores, external systems, or deployment topology in an interactive UI.
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。
Provider-neutral deep-research orchestration for brainstorming, technology choices, comparisons, and state-of-the-art surveys. The Research Lead makes scope and decision calls while native subagents scout, search, verify, synthesize, audit, write, and commit every research artifact.
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。