1.1万 件 ・ 関連度順
概要と使いどころ
Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
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。
GeoToolbox PlaceDescriptor patterns with MapKit integration for location representation, geocoding, and multi-service place identifiers. Use when working with place descriptors, geocoding, or cross-service location data.
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。
MapKit and GeoToolbox skills — PlaceDescriptor patterns, geocoding, and cross-service place identifiers with MapKit integration. Use when working with maps, place data, or geocoding.
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。
Expert knowledge for Azure External Attack Surface Management development including configuration. Use when filtering EASM inventory by ASN, domains, hosts, IPs, pages, SSL certs, or exporting findings to analytics tools, and other Azure External Attack Surface Management related development tasks. Not for Azure Defender For Cloud (use azure-defender-for-cloud), Azure Security (use azure-security), Azure Sentinel (use azure-sentinel), Azure Networking (use azure-networking).
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。
Price and volume tracker for [REPLACE: TOKEN_SYMBOL] with anomaly alerts above [REPLACE: ALERT_THRESHOLD_PCT]% movement
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Provides guidance for writing and benchmarking optimized CUDA kernels for NVIDIA GPUs (H100, A100, T4) targeting HuggingFace diffusers and transformers libraries. Kernels must be kernel-builder/ABI3-compliant: no pybind11, no setup.py, TORCH_LIBRARY_EXPAND bindings only. Supports models like LTX-Video, Stable Diffusion, LLaMA, Mistral, and Qwen. Includes integration with HuggingFace Kernels Hub (get_kernel) for loading pre-compiled kernels. Includes benchmarking scripts to compare kernel performance against baseline implementations.
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 unsure which Higgsfield workspace fits their task, needs to decide between Cinema Studio / Lipsync Studio / Draw-to-Video / Viral Hub presets / Click to Ad / Higgsfield Audio (Sora 2 Trends is built on the retired Sora 2), or is asking 'what should I use for X'. This sub-skill routes by production problem BEFORE model selection.
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 one master design has to become every size a campaign needs — feed, story, reel, cover, and ad placements: the standard size matrix, three strategies of scale-and-crop, re-compose, or rebuild, safe-zone rules, platform crop behavior, and file naming. Trigger on 'resize this design', 'all the sizes', 'adapt to other placements', 'safe zone', 'standard size chart', 'the text gets cut off in stories'. Also use when one visual exists and six placements are waiting on it. Not for — the original concept brief, see `42-image-brief-global`; production steps in Canva or Figma, see `45-design-tool-brief-global`; the full campaign asset list, see `41-campaign-asset-list-global`; an urgent new creative, see `48-quick-visual-brief-global`.
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 show up in OTHER communities without astroturfing — Reddit, Facebook Groups, Discord, Slack, LinkedIn groups, Quora, and niche forums: a prioritized community list with the rules of each space, a named participant roster, post types written in full, reply scripts, a participation calendar, and red lines. Trigger on 'community marketing', 'Reddit marketing', 'seeding plan', 'post in Facebook groups', 'answer questions on Quora', 'we got banned from a group'. Not for — building your OWN paid or private community, see `28-community-building-global`; monitoring mentions across the web, see `15-social-listening-global`; briefing paid creators, see `06-ugc-egc-brief-global`.
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。
Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
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。
Generate, derive, optimize, and diagnose structured AI image prompts for luminous cinematic Eastern xianxia environments under one inherited master canon with measurable divine scale, fixed five-layer space, 40–60% content-bearing breathing air, monumental Eastern architecture, railing-free edges, and coherent immortals and costume. Cover one-location scenic landmarks, immense inhabited celestial realms, cloud-borne palace cities, high-key Eastern sky-megastructure imagery, and the explicit `仙界大境原典` creative route. Use for Chinese fantasy scenery, places where immortals live, heavenly capitals, colossal celestial gates, architectural fragments above cloud seas, measurable divine scale, unusual framing, color and lighting direction, style-preserving variants, prompt rewrites, diagnosis, or direct image generation. Support 16:9, 21:9, 4:3, 3:2, 4:5, and 9:16; default to 16:9 for one prompt and never infer a nine-image series from a vertical ratio.
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。
远程格式化器。用于从huggingface hub的存储库加载数据集。 本SKILL使用依赖data_juicer，请在调用前安装好python环境并安装data_juicer，你可用以下指令进行安装： pip install py-data-juicer 当用户提到加载HuggingFace数据集、远程数据集加载、HuggingFace Hub等需求时使用此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。
Dataspace 文件输出终止算子。用于接收上游算子的单个文件输出，按指定相对目录上传到 Dataspace 空间目录中，实际文件名自动沿用输入文件名。该算子必须作为 DAG 的终止节点使用。
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。
Dataspace 文件输入源算子。用于根据 Dataspace 数据源实例 ID 和空间内文件路径下载单个文件，并将该文件作为工作流输入提供给下游算子。该算子没有上游输入，必须作为 DAG 的起始节点使用。
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。
Train object-detection, image-classification, or SAM segmentation models on Hugging Face Jobs. Use for vision fine-tuning and evaluation; use huggingface-llm-trainer for language 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。
Train or fine-tune language models with TRL or Unsloth on Hugging Face Jobs, including SFT, DPO, GRPO, reward models, and GGUF conversion. Use for cloud LLM training; use huggingface-vision-trainer for vision tasks.
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 recommended Hugging Face models for a task using benchmarks, model size, and device constraints. Use for model selection questions; use huggingface-local-models for GGUF setup and hf-cli for Hub operations.
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。
Initialize a missing research Workspace from the repository template without overwriting existing Run state; use before Pipeline binding when the target under `workspaces/` has no valid core artifacts.
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。
Transform real Chinese architecture and place-based cultural photos into art-directed editorial posters, integrated multi-photo scenes, and optional source comparisons. Use for historic buildings, vernacular streets, culturally rooted shops, interiors, food, travel covers, and place montages; do not use for generic advertising, routine retouching, or invented places.
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。
Capture a full DevTools-protocol trace of any browser automation — CDP firehose, screenshots, and DOM dumps — then bisect the stream into per-page searchable buckets. Use when the user wants to debug a failed run, audit network/console/DOM activity, attach a trace to an in-progress session, or feed structured per-page summaries back into an agent loop so its next iteration learns from the last one.
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。
Own MSBuild import and hook discovery. USE FOR: CustomBefore/CustomAfter hooks, ordered wildcard and NuGet auto-imports, control properties, build/buildTransitive packed layout, package ID and file-name matching, per-TFM forwarders, and tracing why assets or hooks are missing, broken, or replaced. An import guard remains in scope when it is one defect in a broader hook/import flow. DO NOT USE for a focused safety verdict on whether one specific Import needs Exists or is an intentionally unguarded package contract; use msbuild-antipatterns. NEVER INVOKE when imports and hook placement already work and the request is only target Inputs/Outputs, incremental skipping, or FileWrites clean tracking; use incremental-build or target-authoring. Exclude props-versus-targets placement and non-MSBuild systems.
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 a persistent HeyGen avatar — a reusable face + voice identity for the agent, the user, or any named character — powered by HeyGen Avatar V technology. Prompt-based creation by default (description → HeyGen builds it); photo upload is optional for real-person digital twins. Use when: (1) giving the agent a face + voice so it can present videos ("bring yourself to life", "create your avatar", "give yourself an avatar", "design a presenter", "set up an avatar", "let's make an avatar"), (2) the user wants to appear in videos as themselves ("create my avatar", "I want my face in a video", "digital twin of me", "build me an avatar"), (3) building a named character presenter ("create an avatar called Cleo", "design a character named X"), (4) establishing HeyGen identity before making videos — the correct FIRST step when no avatar exists yet. Chain signal: when the user says both an identity/avatar action AND a video action in the same request ("create an avatar AND make a video", "set up identity THEN create a video", "design a presenter AND immediately record"), run heygen-avatar first, then heygen-video. Returns avatar_id + voice_id — pass directly to heygen-video to create HeyGen videos. NOT for: generating videos (use heygen-video), translating videos, or TTS-only tasks.
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。
Manage AgentKit skills, SkillHub/skillhub, skill centers, and skill spaces. Use this skill whenever the user has a management intent for AgentKit skills, skill中心, skill 空间, skill space, or skill hub, including listing, inspecting, downloading, fetching, uploading, publishing, registering, or syncing skills between local directories and remote skill spaces.
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 or maintain Workspace cards, report tabs and Markdown deliverables with consistent styling, working media previews and clear project organization.
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。