「control」の検索結果

Expert knowledge for Azure Osconfig development including troubleshooting, security, configuration, and integrations & coding patterns. Use when running OSConfig via IoT for commands/networking, SSH Posture Control, agent health, or Windows security baselines, and other Azure Osconfig related development tasks. Not for Azure Update Manager (use azure-update-manager), Azure Automation (use azure-automation), Azure Policy (use azure-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。

Expert knowledge for Azure Policy development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when authoring JSON policies, deploying via ARM/Bicep/Terraform, enforcing security baselines, automating with Gatekeeper, or running policy-as-code in CI/CD, and other Azure Policy related development tasks. Not for Azure Blueprints (use azure-blueprints), Azure Role-based access control (use azure-rbac), Azure Resource Manager (use azure-resource-manager), Azure Security (use azure-security).

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 Content Understanding in Foundry Tools development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when building Content Understanding analyzers, RAG document flows, agentic workflows, REST/SDK calls, or GA migrations, and other Azure Content Understanding in Foundry Tools related development tasks. Not for Content Safety in Foundry Control Plane (use azure-content-safety), Azure Speech in Foundry Tools (use azure-speech), Azure AI Vision (use azure-ai-vision), Azure AI Document Intelligence (use azure-document-intelligence).

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 Active Directory B2C development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building B2C user flows/custom policies, configuring IdPs/MFA, securing APIs, automating CI/CD, or monitoring with Sentinel, and other Azure Active Directory B2C related development tasks. Not for Azure Role-based access control (use azure-rbac), Azure Information Protection (use azure-information-protection), Azure Security (use azure-security), Azure Sentinel (use azure-sentinel).

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 images and video through the Higgsfield MCP - text-to-image, text-to-video, and image-to-video with motion control across 100+ models. Generation draws real credits from the connected Higgsfield account; OAuth Connect via the dashboard MCP panel.

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。

Work on a GitHub issue by number for wp-media/wp-rocket. Fetches the issue and hands control to the orchestrator skill (running inline in this conversation), which manages grooming, spec review, implementation, lead review, CI, and QA end-to-end.

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。

Spring Boot best practices and patterns. Use when creating controllers, services or repositories, or when the user asks about Spring Boot layering, wiring, configuration or exception handling. For JPA and Hibernate behaviour, use jpa-patterns instead.

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。

Controls facial expressions in Seedance 2.0 with FACS (Facial Action Coding System) Action Unit codes — muscle-level direction (AU12 = lip-corner puller, AU6 = cheek raiser) instead of emotion labels. Use whenever the user wants precise facial acting, a forced/uncanny/mixed expression, micro-performance in a close-up, monologue or dialogue facial beats, a 'which AU code for anger/fear/disgust' answer, or to generate a FACS reference sheet for a character. Pairs with higgsfield-soul Micro-Expressions (named expressions), higgsfield-audio (dialogue + lip-sync), and higgsfield-gpt-image-2 (the reference-sheet image).

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 whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, Veo, Wan, Seedance, Minimax Hailuo, DoP, Soul, Nano Banana, Seedream, Flux, GPT Image, etc.), camera controls, named motion presets, Soul ID character consistency, Cinema Studio 2.5/3.0, Vibe Motion, troubleshooting failed generations, credit optimization, Photodump, or any mention of higgsfield.ai. Also trigger on generic "write me a video prompt" or "make me an AI video prompt" requests when Higgsfield is the user's configured platform.

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。

Seedance 2.5 prompt director — the omni-reference dialect. Routes the four generation modes (t2v / omni_reference / video_edit / video_extension), writes explicit @Image/@Video/@Audio reference roles with exclusions, stages 30-second videos into end-state beats, and covers video editing, forward/backward extension, first-last-frame and multi-keyframe control, storyboard grids, blockout rendering, and seamless transitions. Use whenever the user asks for a Seedance 2.5 prompt, mentions Seedance 2.5 / Dreamina / Jimeng, wants a clip longer than 15s on Seedance, wants to EDIT or EXTEND an existing video rather than generate a new one, or supplies more than a handful of image/video/audio references. For Seedance 2.0 (4K, `mode=fast`, or a genre hint) use higgsfield-seedance instead.

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 mentions Marketing Studio, DTC Ads, ad video, UGC video, the marketing_studio_video MCP model, or wants to generate one of the 9 Marketing Studio ad presets (UGC, Tutorial, Unboxing, Hyper Motion, Product Review, TV Spot, Wild Card, UGC Virtual Try On, Pro Virtual Try On). Also triggers on hook+setting picklist questions, preset-avatar / custom-avatar / text-generated-avatar handling, 4–15s ad video questions, or any reference to Higgsfield's ad-video product surface. Cross-surface workflow handoffs (GPT Image 2.0 / Soul Cinema / Nano Banana Pro / ms_image image gen → Marketing Studio video) covered in the companion cross-surface-workflow.md. Also use for Ad Multiplier (`ad_multiplier` — 'multiply my ad', many independently edited versions of one supplied 4–30s ad) and for Genjutsu one-off edits of a finished ad (swap one object / product / garment → `hf_mult_replace_object`; transfer motion → `hf_mult_motion_control`).

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 asks about camera movements, shot types, or how to describe camera behavior in a Higgsfield prompt. Contains all named camera controls with descriptions, best use cases, and example prompt phrases.

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。

Guides users through professional filmmaking workflows in Higgsfield Cinema Studio, including creating multi-shot sequences, configuring optical stacks, applying color grading, managing Soul Cast AI actors, and structuring per-scene prompts with Director Panel camera movements. Use when the user mentions Cinema Studio, Cinema Studio 2.5, Cinema Studio 3.0, Cinema Studio 3.5, Cinema Studio 4.0 (`cinematic_studio_video_4_0` — its four modes, camera/lens/aperture/era/genre/pacing ids, light presets, color palette), Soul Cast, color grading, multi-shot video, shot sequences, storyboard workflow, Hero Frame, optical stack, keyframe interpolation, Elements system (@Characters/@Locations/@Props), Speed Ramp, Director Panel, Higgsfield Popcorn, Single Shot / Multi-Shot Auto / Multi-Shot Manual modes, Reference Anchor, Smart shot control, or any professional filmmaking workflow inside Higgsfield.

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。

Reverse JavaScript-based custom DSL/VM interpreters, non-standard WASM-like runtimes, and risk-control engines. Use when analyzing IIFE or switch-based opcode dispatchers, extracting instruction tables, recovering bytecode semantics, capturing VM state at runtime, or reconstructing execution flow.

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 building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control. Treats prompts as code and validates every model output.

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 and download images through APIMart's asynchronous GPT-Image-2 API. Use when Codex needs APIMart image generation, GPT-Image-2 text-to-image, image-to-image with reference URLs or local image files, 1k/2k/4k output, aspect-ratio control, task polling, or saving APIMart image results locally.

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 scroll-controlled cinematic product website with rich motion (动效网站) from product materials, reference pages or videos, and brand assets. Use for requests involving 网站动效, immersive product landing pages where scrolling moves a continuous video forward and backward, multi-scene visual storytelling, direct image2.0 and Seedance 2.0 generation, scene-continuity review, or local preview packaging. Do not use for ordinary corporate sites, dashboards, ecommerce, blogs, or standalone promo videos without a website.

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。

Direct browser control via the Browser Use Terminal CLI. Use when the user wants to automate, scrape, test, or interact with web pages — you drive the browser yourself with Python helpers.

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 generating or editing images from Flutter/Dart with Firebase AI Logic and a Gemini image model (Nano Banana), making the first call work, choosing Gemini Developer API vs Vertex AI, hitting quota, billing or App Check failures, getting empty or image-only responses, sending a user photo as input, controlling aspect ratio or size, writing the image prompt, or deciding what to test.

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。

Weekdays, light browser lane. The one routine in this kit with an outward surface. Takes the slots that are due today, whose drafts were written yesterday and passed the copy check, whose hold box is not ticked, and whose destination the member wrote into the publish allow list themselves, and hands each one to the channel the member configured. It records a receipt the instant each slot lands. It never drives a browser control to publish, never replies, sends only where you released the channel a message, spends only where you released it, and never touches a credential.

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。

Weekdays, conditional browser lane. Reads the ticket ledger and the account, billing, and usage surfaces the member named, and decides which paying customers are about to leave. Every flag is a dossier carrying the trip wires that fired, the exact evidence behind each one, that account's whole history, and one suggested save with its cost and the screen it happens on. It reads billing screens and touches no control on them: a refund, a credit, a plan change, and a cancellation are named and never made.

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 quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell 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。

Database security (encryption, access control, injection prevention), data governance (lineage, quality, MDM), and compliance frameworks (GDPR, CCPA, HIPAA)

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 customers should bring other customers — one-way versus two-way incentives, reward structure and economics, trigger moments, referral messaging, tracking and attribution, fraud controls, and anti-spam compliance by region: TCPA for US, GDPR for EU, PDPA for SEA, LGPD for LATAM. Trigger on 'referral program', 'refer a friend', 'word of mouth', 'viral loop', 'how do I get customers to bring friends', 'affiliate rewards'. Also use when the user has happy customers and no system to use them. Not for — running your own community space, see `28-community-building-global`; posting inside third-party communities, see `38-community-seeding-global`; email flow mechanics, see `14-email-marketing-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。