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概要と使いどころ
Cross-channel content production from an approved idea, brief, notes, transcript, or existing asset. Use when the user wants a ready-to-review draft or a small set of adaptations saved into the bootstrap content workspace. For content strategy use content-strategy-and-planning; for specialist LinkedIn, blog, email automation, SEO, landing page, or campaign work use the dedicated 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。
Aurora Smart Home orchestrator — routing layer for all smart home skills. Use this skill when the user asks ANY smart home question and you need to decide which skill to invoke, or when a task spans multiple skills (e.g., "build a sensor that shows on a dashboard and triggers automations"). Invoke aurora FIRST before reaching for a specific skill — it will route to the right specialist(s) and recommend the correct Claude model to keep token usage efficient. Trigger on: smart home, Home Assistant, ESPHome, automation, IoT, dashboard, ESP32, Node-RED, or any request about controlling or monitoring devices at home.
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。
Godot 4 怪物生成系统，包含波次生成、生成点管理、等级驱动配置和掉落机制。
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。
Unified image-generation engine for the product-shots ecosystem. Dispatches to the right model family (OpenAI gpt-image-2 / Gemini gemini-3-pro-image-preview Nano Banana Pro) with one parameterised script for text-to-image and image-to-image. Primary backend: OmniMaaS / Cloubic gateway (https://api.omnimaas.com/v1); also supports any OpenAI-SDK-compatible gateway via fallback env vars. Auto-resizes oversized reference images to prevent edge-proxy timeouts. Use when the user says "generate an image", "make a picture", "create a visual", "render this", "edit this image", "做一张图", "生成图片", "改这张图" — or when invoked as the image-generation backend by another product-shots skill (main-image / detail-page / ad-creative / social-post / multi-angle). NOT a creative-direction skill: takes a prompt + optional reference images, returns a file path.
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。
UI/UX design intelligence for web and mobile. Includes 50+ styles, 161 color palettes, 57 font pairings, 161 product types, 99 UX guidelines, and 25 chart types across 10 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui, and HTML/CSS). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, and check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, and mobile app. Elements: button, modal, navbar, sidebar, card, table, form, and chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, and flat design. Topics: color systems, accessibility, animation, layout, typography, font pairing, spacing, interaction states, shadow, and gradient. Integrations: shadcn/ui MCP for component search and examples.
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。
Structured idea generation + multi-LLM debate for the product-owner stage. Diverge (generate genuinely different bets), debate (a 4-persona panel on 4 models argues over 2 rounds), converge (synthesize a recommendation). Used by product-owner before architect; available to architect for design-space exploration.
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。
Spawns the decision-scorer agent after architect proposes 2+ variants in an ADR. Produces a weighted scoring table and recommended choice saved to docs/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。
Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to customer opportunities, possible solutions, and experiments. Based on Teresa Torres' Continuous Discovery Habits. Use when the team is unclear what to build next, when multiple opportunities compete, or before writing a PRD for a complex feature space.
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。
How the HyperGrok trading desk works as a team of Grok Bots - roles, seats, shared workspace, evidence standard, approval model and handoff format. Use when setting up the desk, when a Bot is unsure who owns something, or when a request does not fit the normal trade lifecycle.
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。
Bulk-extract many pages from one site or section. Use for "crawl", "everything under /docs", or content spanning linked pages.
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 this skill when visual quality and design identity matter for a PDF. CREATE (generate from scratch): "make a PDF", "generate a report", "write a proposal", "create a resume", "beautiful PDF", "professional document", "cover page", "polished PDF", "client-ready document". FILL (complete form fields): "fill in the form", "fill out this PDF", "complete the form fields", "write values into PDF", "what fields does this PDF have". REFORMAT (apply design to an existing doc): "reformat this document", "apply our style", "convert this Markdown/text to PDF", "make this doc look good", "re-style this PDF". This skill uses a token-based design system: color, typography, and spacing are derived from the document type and flow through every page. The output is print-ready. Prefer this skill when appearance matters, not just when any PDF output is needed.
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。
Remove visible watermarks from user-provided or authorized images, including Gemini sparkle marks, AI-generator corner signatures, and compact high-confidence text watermarks. Use when a user asks to remove, clean, erase, or batch-process visible image watermarks, including requests containing "remove watermark", "去水印", "去除水印", or "水印去除".
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 before generating, editing, or reviewing any user interface — a dashboard panel, a landing page, an email, a slide, an app screen. Sets three deliberate design dials (variance, motion, density) BEFORE generation so the output has a point of view instead of defaulting to the timid, uniform look that reads as "AI made this". Applies to Genesis's OWN dashboard UI, not only things built for others.
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。
End-to-end content creation and publishing. Takes a topic (or generates one), drafts in the user's voice, gets approval via Telegram, and publishes to Medium via browser automation. Invoke with "publish a post about X", "write and publish to Medium", "content-publish", or when an ego-dispatched session needs to create and distribute content.
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。
Builds QA harnesses and agent evals. Use when evaluating tool, trace, red-team, regression, multi-agent, or carried-workspace coding trajectories. Not for metric design (ai-evals).
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 tool and slash-command runtimes for coding-agent CLIs: registries, deferred loading, tool search, dispatch, forks. Use when modeling tool pools. Not approvals or plugins.
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。
Splits a coding task into independent parallel agent workstreams with disjoint write sets, explicit inputs and outputs, dependency ordering, and a merge/review plan. Use when several subtasks can proceed without shared mutable state. Not for tightly coupled edits, one failing root cause, or parallel changes to the same files.
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。
Refresh HitKeep's checked-in bot/AI-agent, IP metadata, and spam-filter datasets through their canonical generators. Use for routine generated-data maintenance; do not use for hand-editing generated assets or changing detector policy.
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。
Web design reference for building production-grade interfaces. Covers layout, typography, color, spacing, shadows, animation, accessibility, responsive design, components, performance, and UX psychology. Use when building UI, reviewing design quality, choosing design tokens, or making any visual design decision.
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 this skill when the user's prompt requires (1) researching a topic across multiple sources, comparing options or alternatives, analyzing trends or history, understanding markets or industries, or reviewing literature or studies and (2) synthesizing that research into a comprehensive, narrative report. If you're planning to search the web or internal knowledge bases, consider using this skill. This skill coordinates research subagents, so use it only when you have a tool for spawning subagents (the Agent or Task tool); otherwise, research the question 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。
End-to-end production workflow guidance for Blender — the order to assemble scenes (block-out → camera → light → forms → materials → detail → render → composite → export), critique protocols, time budgets, and recovery patterns. Use whenever the user asks to "make a complete scene / hero shot / production-quality render", "what's the right order to do this", "set up a full pipeline", or has a multi-step request crossing modeling + lighting + materials + rendering. Make sure to use this skill for any request that spans multiple phases of 3D work, even if the user does not say "workflow" — also covers "make a final image of X", "produce a hero render", "professional-looking result".
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。
Harmonize multiple Blender skills into a coherent pipeline with clear activation precedence, handoff artifacts, dependency gates, and conflict-resolution rules. Use when a Blender task spans several skills, when reference-locked work conflicts with generic production workflow, after adding/updating skills, or when repeated failures indicate skill interference or missing inter/intra-play.
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 turn a static scene, character images, aerial map, drawn path, or route-control image into an immersive first-person FPV AI video prompt, especially Seedance/Kling/Runway/Veo style one-shot videos with numbered stop markers, red-line path control, world-map flythroughs, camera route planning, variable character counts, non-human POVs such as drones, pets, robot vacuums, character references, timed interactions, dialogue, spatial audio, and negative constraints.
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。