「hie」の検索結果

Designs high-performing ad creatives across Instagram, Facebook, TikTok, LinkedIn, Google (Display / Demand Gen), YouTube, Pinterest, and X/Twitter — locking platform dimensions, safe zones, text overlay policy, character limits, industry visual DNA, ad objective hierarchy, composition patterns, CTA strategy, and prompt sanitation. Use when the user says "create an ad", "design an ad creative", "make an ad", "广告创意", "帮我做个广告图", "Instagram ad", "TikTok ad", "Facebook ad", "Google Display ad", "LinkedIn ad", "YouTube ad", "Pinterest ad", "promotional image", "campaign creative", "ad banner", "投放图", or any platform-specific ad request. Routed from `product-shots` when `asset_type == "ad"` or `is_promotion == True`.

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。

Designs, builds, or refactors user-facing web or application interfaces with deliberate visual direction, typography, color and spacing tokens, content hierarchy, responsive behavior, accessible interaction states, and real rendered-surface verification. Use for pages, components, dashboards, landing pages, design systems, and frontend polish. Not for backend logic, API-only work, or visual claims that cannot be rendered or inspected.

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。

Audits an existing rendered interface or frontend diff for hierarchy, content clarity, interaction states, accessibility, responsive behavior, visual consistency, performance-sensitive UI patterns, and anti-generic design defects. Use for a UI/UX review, redesign audit, screenshot review, pre-release visual check, or design-system consistency pass. Not for building a new interface from scratch or for backend-only review.

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。

Designer's eye QA: finds visual inconsistency, spacing issues, hierarchy problems, AI slop patterns, and slow interactions — then fixes them. (gstack)

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 metacognitive checkpoints that prevent AI-assisted learning from bypassing genuine understanding. Use when students use AI tools and may overestimate their own comprehension.

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。

Coordinates UDL and differentiation tools through a universal-first hierarchy: barrier removal before targeted differentiation before individualised accommodation. Use when planning accessible learning.

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。

Classify curriculum content into Know, Understand, and Do categories to align teaching and assessment approaches. Use when planning units, writing objectives, or selecting assessment methods.

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。

Map the epistemic structure of a subject to determine knowledge types and inform curriculum sequencing. Use when designing courses, restructuring programmes, or analysing knowledge architecture.

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。

Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence about the underlying intent. Use when an ask is underspecified ("build me X" without "for whom" or "why now"), when the user explicitly invokes ("interview me", "grill me", "are we sure?", "stress-test my thinking"), or when you catch yourself silently filling in ambiguous requirements before any plan, spec, or code exists.

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, preview, implement, and assess mini-program interfaces against an approved prototype, screenshot, visual reference, design system, or bounded UI request while preserving product semantics and existing accepted behavior. Use when users ask to reproduce a mini-program screen, refine visual hierarchy, adapt layouts across device sizes, handle safe areas or keyboards, inspect touch targets, scrolling, media, or gesture conflicts, compare an implementation with a reference, or prepare a device-verification matrix. Separates proposed visual previews, user approval, source integration, local checks, and real-device evidence; never invents product functionality for visual completeness or claims device validation without device-specific proof.

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, deepen, validate, index, and maintain a private hierarchical career knowledge graph from supplied career materials. Use when the user asks to create or update a VitaeGraph, model education with nested courses or thesis work, enrich projects from Git repositories, or supply deep selected career context to another VitaeContext 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。

Build, normalize, and maintain the user's Career Context file so downstream platform outputs stay factual and consistent. Use when the user wants an agent to consolidate CV data, LinkedIn exports, GitHub history, project summaries, bio facts, achievements, or positioning into one professional source of truth before editing platform-specific assets.

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。

Sichtbarkeit, Zitierung und Empfehlung in KI-Antwortsystemen für Deutschland und den DACH-Raum evidenzbasiert prüfen und verbessern. Nutze diesen Skill, wenn eine Marke oder Seite in KI-Overviews, ChatGPT, Perplexity, Gemini oder Copilot auftauchen soll, wenn Crawler-Freigaben für KI-Bots, llms.txt, strukturierte Daten oder die Extrahierbarkeit von Inhalten zu bewerten sind, oder wenn jemand nach AEO, GEO oder LLMO fragt. Trennt Abruf, Zitierung, Erwähnung und Empfehlung, prüft Behauptungen über KI-Rankingfaktoren gegen Primärquellen und verspricht keine Sichtbarkeit. Für klassisches technisches SEO ist seo-audit zuständig.

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。

Diagnose problems before solving them: turn "X is broken and we don't know why" into a precise problem statement, verified root causes, solutions traced to those causes, and a rollout plan. Use whenever the user reports something failing, breaking, slowing, or recurring without a known cause: "sales dropped and we don't know why", "this keeps happening", "why does X keep failing", "find the root cause", "run a post-mortem", "5 whys"; Vietnamese "sao cứ bị vậy hoài", "tìm nguyên nhân gốc", "X đang hỏng mà không rõ vì sao". Trigger even when the user asks for solutions directly: "give me ideas to fix falling sales" is a diagnosis request. Not for open-ended ideation when nothing is broken (brainstorm-coach), understanding user needs (design-thinking), or company-level strategic bets (strategy-board).

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。

Act as an end-to-end data scientist: turn business questions into defensible analysis, validated models, and decision-ready reports. Use whenever the user asks to analyze, explore, or profile a dataset or CSV/Parquet/Excel file; asks what drives a metric or why a number changed ("why did churn go up?"); wants to test whether a difference is real (A/B tests, experiments, "is this significant?", "how many samples do I need?"); wants a predictive model (churn, forecast, scoring, segmentation, classification, regression); asks to review an existing analysis, notebook, or model for flaws; or needs results written up for decision-makers. Triggers in any language ("phân tích dữ liệu", "xây model dự đoán", "kiểm định A/B"), even when they never say "data science" or "statistics".

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。

Read, study, and answer questions about long books and papers without loading the whole text into one context window, keeping page-anchored notes as a reusable workspace. Use whenever the user asks to read, study, summarize, analyze, review, or answer questions about a long book, textbook, PDF, EPUB, thesis, dissertation, survey paper, or any document of roughly 50+ pages, in any language (Vietnamese "đọc sách", "tóm tắt sách", "phân tích luận án"). Also use when a `{slug}-notes/` workspace from a previous session sits next to a source file and the user asks a follow-up question about that book. Not for short documents (under ~30 pages) that fit in context; read those 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。

Score candidate CVs on a 100-point scale against a Job Description. Use this skill when the user wants to evaluate, score, rank, or screen candidate CVs/resumes against a JD. Also trigger when the user mentions 'review CV', 'screen resume', 'rate candidates', 'shortlist', or any context involving matching resumes to job requirements.

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 rigorous, citation-backed desk market research: quick go/no-go market scans, market sizing (TAM/SAM/SOM), competitor analysis, customer demand signals, and trend/macro (PESTEL) analysis. Use this skill whenever the user wants to research, size, validate, or enter a market — "is there a market for…", "how big is the market for…", "who are the competitors of…", "should I build/launch/sell…", "validate this business idea", "market research for…", "market entry" — in any language and for any country's market (e.g. "nghiên cứu thị trường", "étude de marché", "市場調査", "análisis de mercado"), even when the user never says the words "market research". Also use it when another skill or workflow (strategy-board, design-thinking, a product brief) needs external market facts delivered into its fact base or research folder.

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 and explain bmad-loop run artifacts under `.bmad-loop/runs/`. Use for live health checks ("is it stuck?", "is the loop alive?", "what is the agent doing?") and post-run forensics ("what happened?", "why did story X fail?", "where did the tokens go?"). Also triggers on "monitor/check/summarize the loop", "why did the run pause?", Vietnamese "theo dõi bmad loop", "phân tích run", "đọc log của run", and equivalent requests in other languages. Use only for bmad-loop's own run artifacts, not application runtime logs or CI-provider build logs.

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。

Plan and run manual tests of the project's running app. Runs a session in one of five modes: exploratory, verification, smoke, assessment (UX, localization, accessibility, improvement review), or AI probe. Also writes a manual test plan that holds only what automated tests cannot judge. Use whenever the user asks, in any language, for something to be tested by hand or for a manual test plan — "manual test", "exploratory test", "bug hunt", "verify the bug fix", "smoke test", "QA this screen", "review this screen's UX", "what would you improve", "check the localized copy", "test the AI agent's answers", "write manual test cases", "kịch bản test manual" — or assigns a test design, test plan or test-case IDs to execute by hand. Not for writing automated tests.

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。

Act as a product-manager copilot that turns evidence into product decisions and artifacts: backlogs and prioritization, PRDs and user stories, metrics and OKRs, experiments, launch plans, feedback triage, and pricing/packaging, kept in a per-product workspace. Use whenever the user wants to decide what to build, spec it, or ship it: "write a PRD for…", "prioritize our backlog", "what should we build next", "plan OKRs", "define our north star metric", "design an A/B test", "plan the launch", "triage this customer feedback", "platform or feature?", in any language ("viết PRD", "ưu tiên tính năng nào", "quản lý sản phẩm", "プロダクト管理", "产品经理"), even when they never say "product manager". Also use when the user returns to a product workspace this skill created (a directory holding `product.md`, `state.md`, and `decisions.md`). Not for deep user discovery (design-thinking), desk market facts (market-researcher), or company-level bets (strategy-board).

Coach structured brainstorming sessions on any topic: diverge on ideas together, then converge on priorities and next steps in a session document. Use whenever the user wants ideas or wants to think out loud, in any language ("brainstorm with me", "give me ideas for…", "help me come up with…", "let's explore options for…", "I'm stuck on the name / the features"; Vietnamese "brainstorm cùng tôi", "cho tôi ý tưởng", "nghĩ cùng tôi xem"), even when they never say "brainstorm". Also use when the user wants multiple perspectives or a devil's-advocate pass on their ideas ("give me different angles", "phản biện mấy ý tưởng này", "party mode"). Not for diagnosing why something is failing (problem-solver), user research (design-thinking), or company-level strategic bets (strategy-board).

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。

A complete fiction-writing studio, run as a team of named specialist agents, that guides an author from a bare idea to a polished prose manuscript. Use this skill whenever the user wants to write, plan, or revise fiction — a novel, novella, short story, or series. Trigger on requests like "help me write a novel", "I have an idea for a story", "develop my characters", "build a world for my fantasy", "outline my plot", "fix this scene", "my dialogue feels flat", "give me beta-reader feedback", or any time the user is doing creative storytelling and would benefit from structured, craft-aware guidance. Also trigger when the user names a studio member (Homer, Aristotle, Fyodor, Tolkien, Scheherazade, Oscar, Max, Virginia, Borges, Bloom) or asks to switch creative roles / bring in a specialist.

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。

Write, restructure, classify, and review documentation with the Diataxis framework. Use when the user asks to create, improve, audit, or reorganize documentation of any kind: knowledge bases, help centers, onboarding guides, process docs, manuals, runbooks, product or API docs, tutorials, how-to guides, references, explanations. Also use when the user mentions Diataxis, docs taxonomy, or documentation architecture, or asks why a document feels confusing. Also use for Simplified Technical English (ASD-STE100) or controlled-language rewrites of English technical docs. Not for marketing, legal, sales, press, or fiction writing unless the user wants a Diataxis-style 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。