192 件 ・ 関連度順
概要と使いどころ
Turn real customer reviews, quotes, and case-study results into polished social-proof videos built in HyperFrames -- single-testimonial spotlights, review-wall montages, and stat-driven proof reels with captions and voiceover, cut for vertical, square, and wide. The highest-converting content most businesses never make.
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。
Operate Baichuan-7B model loading, architecture inspection, C-Eval/MMLU evaluation preflights, and DeepSpeed pretraining setup from self-contained repo guidance.
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。
Turn long videos & livestream VODs into viral vertical shorts, 100% locally — on-device transcription, LLM highlight detection, 9:16 reframe with karaoke captions, and a per-clip render-QA report. Use when the user asks to clip / cut / 切片 / 剪 a long video, podcast or stream replay into short clips, find highlights / 爆点 in a video, or transcribe a media file. Footage never leaves the machine.
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。
Mathematical visualization skill for equations, proofs, and geometric concepts. **Triggers when:** - User mentions equations, formulas, or mathematical expressions - Request involves mathematical proofs or derivations - Content includes geometric relationships - User mentions LaTeX, calculus, algebra, geometry, trigonometry - Patterns: "equation", "formula", "prove", "derive", "graph", "plot" **Capabilities:** - LaTeX equation rendering with color-coded components - Function graphing and transformations - Geometric constructions and proofs - 3D mathematical surfaces - Step-by-step derivations with highlights
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 comprehensive marketing content for themes, plugins, and web products. Generates organized folder structure with product descriptions, feature highlights, social media posts, email campaigns, video scripts, sales materials, and brand assets. Use when creating promotional content, announcements, or sales copy.
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。
Detect semantic-level bugs by analyzing whether code behavior matches its intended purpose inferred from function/variable names, comments, docstrings, and documentation. Use when users need to: (1) Find logic errors where implementation contradicts stated intent, (2) Identify off-by-one errors and boundary mismatches, (3) Detect inverted logic or wrong operators, (4) Catch missing edge case handling, (5) Verify code matches its documentation. Highlights mismatches between intent and implementation across multiple programming languages.
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。
Performs abstract interpretation to produce summarized execution traces and high-level program behavior representations. Highlights key control flow paths, variable relationships, loop invariants, function summaries, and potential runtime states using abstract domains (intervals, signs, nullness, etc.). Use when analyzing program behavior, understanding execution paths, computing loop invariants, tracking variable ranges, detecting potential runtime errors, or generating program summaries without concrete execution.
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。
Compare evaluated runs in a retort experiment along factor dimensions. Surfaces effects of each factor, aggregates across replicates, and highlights cells that diverge qualitatively — complementing (not replacing) retort's ANOVA 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。
Use when an agent must make TwelveLabs do real video-understanding work: indexing footage, semantic/visual search across an archive, generating descriptions, summaries, chapters, highlights, and tags from video, producing multimodal embeddings, or wiring TwelveLabs into a media-production pipeline (NLE panels, logging, compliance review, metadata). Covers the current model families (Marengo for search/embeddings, Pegasus for video-to-text analysis), the v1.3 Video Understanding API (indexes, assets, tasks, search, analyze, embed), prompt construction for analysis, capability and format limits, pricing/quota math, output quality review (hallucination and timestamp accuracy), and privacy/rights obligations when footage shows real people. Not for generating or editing video pixels — this is analysis and retrieval.
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-independent lighting direction for AI-generated images, video clips, ads, film scenes, avatars, product shots, interviews, beauty work, and social content. Use when an agent must specify, translate, maintain, troubleshoot, or QA motivated lighting, key/fill/back/rim/practical lights, hard or soft light, color temperature, exposure, contrast, time-of-day, continuity, reference strategy, or safety/accessibility risks in generated media.
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 luxury-automotive brand whose marketing surfaces read as cinematic editorial. The base canvas is **near-black** (`#181818`) holding pure white display type; white-canvas bands appear only inside specific editorial contexts (preowned listings, pricing tables). The single brand voltage is **Rosso Corsa** (`#da291c`) — the iconic Ferrari racing red — used scarcely on primary CTAs, the Cavallino mark, and Formula 1 race-position highlights. Type runs **FerrariSans** at modest weights (display 500, body 400) — never bombastic. Spacing follows an explicit 8px token ladder (`xxxs` 4px through `super` 128px); generous editorial pacing throughout. The brand's strongest visual signature is the **full-bleed cinematic hero photograph** that fills the viewport top with car photography, model details, or trackside livery — followed by a tighter editorial body layout below.
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 an agent needs to make a HyperFrames video of a Strudel live-coding track, where the code itself is the picture and every token lights up on the note it plays. Trigger on: "strudel video", "live coding video", "show my code playing", "make a video of this track with the code", "prod by claude". Covers composing the track, recording it offline from pinned Strudel, and building the 1080x1080 video (typed opener, parts powering on, real Strudel theme switches, graffiti ASCII drops, typed sign-off).
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。
Generates MLS-ready property listing descriptions with attention-grabbing headlines, feature highlights, neighborhood context, and SEO keywords across multiple buyer-persona styles
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。
Automate Blender rendering from the command line. Use when the user wants to set up renders, batch render scenes, configure Cycles or EEVEE, set up cameras and lights, render animations, create materials and shaders, or build a render pipeline with Blender Python scripting.
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。
Draws an activity flow / system architecture diagram as ONE self-contained, INTERACTIVE HTML+SVG page (2-pane app layout — left: diagram, default fit-to-view with zoom/pan; right: sidebar with explainer cards), styled like a real hand-drawn enterprise doc (Stripe/AWS-docs style — real brand logos for MongoDB/Odoo/n8n/etc. from a bundled Simple Icons library, neutral white boxes, sans-serif, no "AI neon" look), scroll-to-zoom, auto light/dark with a toggle button — clicking a flow (a legend chip, a line, or a step badge) highlights that flow with traveling dots along the arrows in their direction, a ping at the destination box, and a sidebar panel that slides out, while everything else dims; two-way arrows (OUT = solid blue / RETURN = dashed green) carry numbered step badges, colored by semantic meaning (red = auth checkpoint, purple = scheduled flow, amber = data pipeline), a small "hop" arc where two lines are forced to cross, dashed group regions, one explainer card per flow in the right sidebar. Use this skill ANY TIME the user wants to "draw a diagram", "draw a flow", "draw a system diagram", "redraw this so it's easier to follow", "interactive diagram", "two-way diagram", "request/response flow", "make a free-form HTML diagram" — even if they never say the word HTML. Especially good when both the request direction AND the response direction need to be shown, or when a templated tool (archify, mermaid) is too rigid. Do NOT use for data charts (bar/line/pie), and do not use when the user asks specifically for archify or mermaid.
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。
Animate objects, cameras, lights, and properties in Blender — keyframes, F-curves, easing (Bezier, Linear, Sine, Bounce, Elastic), shape keys (morph targets / blendshapes / visemes), drivers (Python expressions on properties), NLA actions for reuse and layering. Use whenever the user asks to "animate this", "make it move / rotate / scale over time", "add keyframes", "loop / oscillate", "shape key / morph / blendshape", "visemes for lip sync", or any time-based property change. Make sure to use this skill even if the user does not say "animate" — also covers "spin it slowly", "make it wave", "fade in / out", "pulse", "facial expression".
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。
Amazon reverse product selection: filter Amazon niches and keywords by 30+ business dimensions (market size & growth, price tiers & share, competition density & top concentration, demographics such as age/gender/income, review highlights & pain points) from a metrics pool aggregated from historical business insight reports. Trigger when users mention reverse product selection, metrics filtering, niche reverse lookup, blue ocean niche discovery, low-competition niche, newcomer-friendly niche, brand-fragmented market, pain-point entry, feature reverse lookup, pricing tier opportunity, demographic-based selection, or similar terms. Even if the user does not explicitly say "reverse product selection," trigger this skill whenever the request involves filtering Amazon niches that match specific business criteria.
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。
amazon-listing-doctor是由buluslan（公众号：新西楼.AI）研发的亚马逊Listing质检Skill，他会基于 CDQ算法 / A9 / COSMO / Alexa 四大底座知识，来给Listing进行全身体检和打分，输出一份诊断报告，帮你揪出"流量加倍、弯道超车"的机会点。 更多跨境电商 AI 实战内容，请关注公众号「新西楼.AI」。 Audits Amazon listing health across CDQ / A9 indexability / COSMO intent-coverage / Alexa discoverability, plus 2026 compliance rules (title 75-char, highlights 125-char, image defects). Pure diagnosis, zero dependencies, works offline. Trigger whenever the user mentions checking/auditing/scoring/diagnosing an Amazon listing's quality — in any language; 中文卖家说 listing 体检 / 质检 / 打分 / 诊断 / 健康度 / 质量分 时同样适用。
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。
Create, run, schedule, or debug MotherDuck Flights, Python jobs executed on MotherDuck compute.
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。
Instagram 公开社交数据查询与内容分析 skill，通过 MaxHub API 查询帖子/Reels/Stories/Highlights、评论、点赞列表、用户资料、粉丝/关注、搜索、标签和相关内容。适合海外社媒运营、KOL 画像、内容互动分析、竞品跟踪和趋势研究。默认 read-only，侧重公开或用户授权范围内的数据；agent 应优先使用 recipes 进行单端点或链式调用，并避免采集超出用户授权的个人信息。所有请求发送到 https://www.aconfig.cn。
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 高教社杯/CUMCM/电工杯 mathematical modeling abstracts, keywords, highlights, first-page claims, or high-density summaries need drafting, revision, audit, or style diagnosis, especially when feedback mentions too many numbers, weak focus, process-listing, empty official prose, buzzwords, missing structure, weak keywords, unsupported values, or first-page claim verification.
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。
Entry point for reading PANews cryptocurrency / blockchain news, market narratives, and Polymarket smart money leaderboards. Triggers: today's headlines, breaking news, trending rankings, article search, reading specific articles, browsing columns / series / community topics, industry events & conferences, event calendar, platform hot searches and editorial picks, latest smart money boards, board highlights, and board comparisons.
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。
Creates sell-side CIMs with business description, financial overview, growth drivers, and investment highlights. Use when preparing sell-side marketing materials, writing CIMs, or positioning companies for sale.
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。