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Advanced CV for infrastructure inspection including forest fire detection, wildfire precondition assessment, roof inspection, hail damage analysis, thermal imaging, and 3D Gaussian Splatting reconstruction. Expert in multi-modal detection, insurance risk modeling, and reinsurance data pipelines. Activate on "fire detection", "wildfire risk", "roof inspection", "hail damage", "thermal analysis", "Gaussian Splatting", "3DGS", "insurance inspection", "defensible space", "property assessment", "catastrophe modeling", "NDVI", "fuel load". NOT for general drone flight control, SLAM, path planning, or sensor fusion (use drone-cv-expert), GPU shader development (use metal-shader-expert), or generic object detection without inspection context (use clip-aware-embeddings).

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 your Korea experience — Seoul's palaces and K-pop culture, Busan's beaches, Jeju Island's nature, Korean BBQ crawls, and K-beauty shopping. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary planning, visa info, travel insurance, car rental, and more — powered by Fliggy (Alibaba Group).

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。

Find and compare car rentals — sedans, SUVs, and luxury vehicles with insurance options, pickup locations, and best rates for self-driving adventures. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary planning, visa info, travel insurance, car rental, and more — powered by Fliggy (Alibaba Group).

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。

Manipulate row selection (`df.selection`) on a Datagrok DataFrame via the datagrok_exec tool — set, clear, invert, add to, remove from, intersect, and read the selection mask. Also covers current row (`df.currentRowIdx`), the cross-skill bridges to/from the filter, and how to materialize the selected rows as a new DataFrame. Use whenever the user says "select rows", "deselect", "invert selection", "highlight rows", "selected rows", "clear selection", "current row", "currentRowIdx", "count selected", "list selected indexes", "selection from filter", "filter from selection", or asks for selected rows as a new table. Does NOT cover row filtering (separate skill `datagrok-filtering`) or generic DataFrame cloning (`datagrok-df-and-columns`).

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。

Lighthouse audits and Core Web Vitals — LCP, CLS, INP. Use when optimising page load, layout shift, input delay, images, fonts or render-blocking resources.

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。

Light, dark or both, and when a theme selector is worth it. Use when defining a base palette or deciding on dark mode support.

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。

Metallurgy of the major nonferrous structural and engineering alloys — aluminum, copper, titanium, nickel, magnesium, and their strengthening mechanisms. Covers precipitation (age) hardening in Al-Cu and Al-Zn-Mg systems, solid-solution strengthening in brass and bronze, alpha-beta titanium, nickel superalloys with gamma-prime, and the trade-offs in density, strength, corrosion resistance, and cost that decide when to leave steel for a lighter or more specialized metal.

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。

Stellar spectral analysis from first light to chemical abundance. Covers continuum emission and absorption, the OBAFGKM classification sequence, luminosity classes, line identification, Doppler shifts, curve-of-growth abundance analysis, and the astrophysical conclusions that follow from a spectrum. Use when classifying a star, measuring radial velocity, inferring composition or temperature, or teaching why the Sun is mostly hydrogen.

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。

Practical naked-eye and binocular sky observing. Covers dark adaptation, limiting magnitude, constellation recognition, star hopping, the messier and Caldwell catalogs accessible without a telescope, the Moon, planets, meteor showers, aurorae, and the ethics and habits of observing under light-polluted and dark skies. Use when teaching someone to find their way around the sky, planning a naked-eye session, or choosing a first binocular tour.

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 GSD commands are failing or .planning/ artifacts look inconsistent. Run before any GSD execute-phase or verify-work attempt to catch cross-artifact mismatches early.

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。

直播切片：从电商直播录屏中找出高光片段（按时间戳 / 按字幕关键词 / 按停顿自动提议），批量导出 9:16 竖屏切片，自动模糊填充横屏画面、烧录标题与字幕、响度标准化，并给切片写标题与开头钩子。Use when the user has a livestream recording and wants 直播切片, 切片, highlights, clips, 高光片段, repurpose a live stream into short videos for 抖音 / 视频号 / TikTok.

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。

字幕与花字：为带货短视频生成 ASS/SRT 字幕与花字（大标题弹出、关键词高亮、贴纸标签、行动号召按钮），自动避开平台底部/右侧 UI 安全区，并用 ffmpeg/libass 烧录。Use when the user wants subtitles, captions, 字幕, 花字, 大字报, keyword highlight, burned-in captions, SRT/ASS files, or text overlays that don't get covered by TikTok/抖音 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。

Image generation, photo editing, background removal — transparent PNG images, cutouts, ecommerce packshots, product catalogs, lifestyle shots via Bria.ai. Build store-ready e-commerce catalogs at scale — shadows, product dimensions images, lifestyle scenes, marketplace listing variants. ALWAYS use this skill when the user wants to generate, edit, or transform any image — hero images, banners, social media visuals, product photos, illustrations, icons, thumbnails, ad creatives, or marketing materials — or to build a product catalog, create a packshot, stage a lifestyle shot, remove a background, make transparent PNGs, or batch-process product photos. Triggers on packshot, product catalog, product shot creator, lifestyle shot, cutout, product dimensions image, inpainting, outpainting, object removal, upscale, photo restoration, style transfer, relight, reseason, sketch-to-photo. Commercially safe, royalty-free.

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。

Maximum control over AI image generation — write structured VGL (Visual Generation Language) JSON that explicitly controls every visual attribute. Define exact object placement, lighting direction, camera angle, lens focal length, composition, color scheme, and artistic style as deterministic JSON instead of ambiguous natural language. Use this skill when you need reproducible image generation, precise control over scene composition, or want to convert a natural language image request into a structured JSON schema for Bria FIBO models. Triggers on requests for structured prompts, controllable generation, VGL JSON, deterministic image descriptions, or Bria/FIBO structured_prompt format.

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 claiming the AI bounty on the tDVV mainnet sidechain. This public claim skill now supports Portkey AA/CA only, requires CA sync and holder preflight before any write, and routes to AA/CA onboarding, AA/CA claim, or diagnostics-only stop handling.

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。

Decide whether to adopt, adapt, or justify building a new script, tool, utility, library, module, dependency, or bespoke capability. Use in task planning, worker execution (including tooling discovered after planning), or code review when an implementation choice may duplicate an existing solution.

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。

Augmented reality (AR) reality tech. Passthrough overlays, hit-test/anchors, occlusion, lighting, camera permissions, and safety.

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。

Assess and address review feedback on GitHub PRs, GitLab MRs, or in conversation. Use when checking new reviews, responding to comments, rechecking after a push, or following up on approvals and change requests.

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。

Summarize files or a requested directory scope from actual contents. Extract code, config, data and document evidence, preserve exact counts and source locations, and disclose incomplete or unsupported acquisition. Use for file summaries, code explanations and configuration overviews.

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 reviewing, designing, or improving a workshop, lesson, training session, facilitation plan, talk, or educational explanation. Use it when the user provides a topic, concept, or explanation and wants better framing questions, curiosity hooks, opening prompts, discussion questions, learner reflection prompts, or ways to make participants think before being taught.

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 explicitly asks Rewrite Room to route documentation work, or when audit/sync/freshness, user-facing authoring, citation-driven writing, docs-to-skill conversion, and AI-instruction optimization overlap and exactly one workflow must be chosen.

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 an application needs to store config, data, cache, or state files. When designing where user-specific files should live. When code writes to ~/.appname or hardcoded home paths. When implementing cross-platform file storage with platformdirs.

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。

Illustrative Claude Code skill configuration. Use when learning the basic SKILL.md shape; follow the canonical runtime reference for the current field inventory.

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 edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' 'copy sweep,' 'tighten this up,' 'this reads awkwardly,' 'clean up this text,' 'too wordy,' or 'sharpen the messaging.' Use this when the user already has copy and wants it improved rather than rewritten from scratch. For writing new copy, see copywriting.

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。