「ics」の検索結果

Bevy ECS skill for 2D physics. Keywords: Bevy, physics, 2D, ECS, collision.

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。

Bevy ECS skill for 3D physics. Keywords: Bevy, physics, ECS, 3D.

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。

Bevy ECS skill for logs and diagnostics. Keywords: Bevy, LogPlugin, DiagnosticsPlugin, FrameTimeDiagnosticsPlugin.

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 blueprint for sports games (FIFA, NBA 2K, Rocket League, Tony Hawk) covering physics-based ball interaction, team AI formations, contextual input, and match umpire/score authority. Broadcast framing routes to godot-camera-systems. Use when building soccer, basketball, hockey, racing sports, or arcade sports games. Keywords ball physics, magnus effect, formation AI, team tactics, contextual controls, steering behaviors.

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 blueprint for player mortality loops: progress-index checkpoints, soul graves, ghost/spirit layers, I-frame restitution, world-progress persistence, and death analytics. Use when implementing respawn, shrine checkpoints, corpse-run retrieval, or second-chance mechanics. Keywords revival, respawn, checkpoint, soul grave, ghost mode, I-frames, death analytics, progress index.

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。

Bevy ECS skill for 2D physics. Keywords: Bevy, physics, 2D, ECS, collision.

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。

Bevy ECS skill for 3D physics. Keywords: Bevy, physics, ECS, 3D.

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。

Bevy ECS skill for logs and diagnostics. Keywords: Bevy, LogPlugin, DiagnosticsPlugin, FrameTimeDiagnosticsPlugin.

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。

Best-practices reference for preparing and instrumenting applications on Temps. Covers the app runtime contract (`.temps.yaml` health, HOST/PORT, readiness, SIGTERM, replicas, migrations) and production observability (errors, traces, metrics, logs, analytics, privacy, sampling, cardinality, credential boundaries). Use whenever building or reviewing an app for Temps, configuring health checks, adding telemetry, diagnosing missing/noisy signals, or checking OTLP/Sentry/analytics ingestion. Triggers include "temps best practices", "prepare this app for Temps", ".temps.yaml health", "temps health check", "ignore health checks in otel", "temps observability", "wire up telemetry", and "instrument this app for temps". Prefer focused setup skills for a single SDK. Use temps-cli for executing deploy and resource-management commands.

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 protocol-based analytics infrastructure with swappable providers (TelemetryDeck, Firebase, Mixpanel). Use when user wants to add analytics, track events, or set up telemetry.

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。

omicsViewer visualizes ExpressionSet (or SummarizedExperiment) in an interactive way. The omicsViewer has a separate back- and front-end. In the back-end, users need to prepare an ExpressionSet that contains all the necessary information for the downstream data interpretation. Some extra requirements on the headers of phenotype data or feature data are imposed so that the provided information can be clearly recognized by the front-end, at the same time, keep a minimum modification on the existin

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。

The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor

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 Synapse Analytics development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing Synapse workspaces, SQL/dedicated pools, serverless SQL, Spark pools, or Synapse Link for Cosmos DB, and other Azure Synapse Analytics related development tasks. Not for Azure Data Factory (use azure-data-factory), Azure Data Explorer (use azure-data-explorer), Azure Databricks (use azure-databricks), Azure HDInsight (use azure-hdinsight).

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 Energy Data Services development including troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when configuring ADME metrics/partitions, choosing tiers, securing auth/ACLs/legal tags, or integrating ACZ/DDMS with Databricks/Fabric, and other Azure Energy Data Services related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Factory (use azure-data-factory), Azure Data Manager for Agriculture (use azure-data-manager-for-agri).

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 Brand Analytics interpretation and strategic insights for Brand Registry owners. Decode Search Frequency Rank (SFR) data, analyze Market Basket patterns, interpret Item Comparison reports, and extract demographic insights to optimize product strategy and advertising spend. Works with Brand Analytics data from all Amazon marketplaces. Requires Brand Registry access. Use when: (1) analyzing Search Frequency Rank data for keyword opportunities, (2) interpreting Market Basket data for cross-sell and bundling, (3) understanding Item Comparison competitive positioning, (4) extracting customer demographic insights, (5) optimizing product portfolio based on customer behavior, (6) building data-driven advertising strategies.

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。

Define KPIs, metrics, and tracking systems to measure brand health, awareness, perception, and equity over time. Use when the user says "brand measurement", "brand metrics", "how do we measure the brand", "brand KPIs", "brand health tracking", "brand awareness metrics", "brand equity measurement", "is our brand working", "brand ROI", "brand performance", "brand tracking", "brand health score", "prove brand value", "brand dashboard", or needs to show stakeholders whether brand investment is delivering results.

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。

Writes the character-performance layer of a video prompt as behavior under pressure, not displayed emotion — objective, obstacle, tactics, beats, subtext, listening, body/status/proxemics, and mandatory eye life. Produces a reusable 150–220-word acting master profile per character plus a per-scene rewrite of it, and a locked voice prompt. Use whenever a prompt needs acting, performance, or emotion direction; whenever characters read wooden, dead-eyed, or 'AI'; whenever a character must stay themselves across many shots; or when the user asks for character behavior, mannerisms, tics, a gait, or how someone reacts. Pairs with higgsfield-facs (muscle-level AU codes) and higgsfield-seedance (the prompt the paragraph goes into).

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 motion-design / animated-ad creation flow on Higgsfield via the MCP connector. Use when the user wants to create motion design, animate a logo, make a video from an image, build an animated ad or brand promo, turn a product into motion, or says 'make a motion', 'motion design', 'animate this', 'make a video from my logo', 'animated brand', 'motion graphics', 'brand motion', 'kinetic graphics', 'promo video', or 'ad video'. Drives a storyboard-first pipeline: brief → storyboard sheet (GPT Image 2) → video (Seedance 2.0) — an AI-generated pixel video clip. Distinct from higgsfield-motion (the named camera/motion preset library) and from higgsfield-vibe-motion (deterministic Remotion code with crisp text); use vibe-motion instead when the text/logo must stay perfectly crisp, editable, and deployable as code.

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 Vibe Motion, motion graphics, kinetic typography, animated text, brand animations, logo animations, infographic animation, presentation animation, data-driven video, or prompt-to-motion-graphic workflows. Vibe Motion is fundamentally different from video generation — it creates deterministic code-based motion graphics, not AI-predicted pixel sequences. Use this when the text/logo must stay perfectly crisp and editable (code). For a cinematic/kinetic AI-generated video ad built from a storyboard (pixel render, native audio), use higgsfield-motion-design 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。

Analyze website traffic, global rank, engagement metrics, and traffic sources for any domain. Use this skill to evaluate affiliate program websites, compare competitor traffic, assess advertiser strength, or understand where an audience comes from. Triggers on: "analyze traffic for [domain]", "how much traffic does [site] get", "compare traffic between [site A] and [site B]", "is [program] worth promoting based on traffic", "traffic analysis", "website analytics for [domain]", "where does [site] get traffic", "check if [advertiser] is legit", "evaluate [program] website health", "SimilarWeb analysis", "traffic sources for [domain]", "how popular is [site]", "website rank", "domain authority check", "compare affiliate program websites".

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。

Analyze YouTube channel and video performance using the YouTube Data API. Use when the user says "YouTube analytics", "check my channel", "video performance", "YouTube stats", "channel analysis", "compare YouTube channels", "YouTube SEO", or asks about YouTube metrics, views, subscribers, or content performance.

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。

Add a measured sound pass to a motion-graphics video made with Claude Code (HyperFrames, Remotion, GSAP, Claude Motion or the motion-broll skill). Builds a cue list, checks the music's beat grid against the kick drums, lands cuts on the beat, places one real sound effect per cue from a bundled CC0 library, mixes to -16 LUFS with true peaks below -4 dBFS measured on the exported MP4, and proves it with frames, waveforms and 5 timestamps for a human to check. Use when someone wants sound effects, sound design or music added to a motion-graphics video, or says their AI video sounds like cheap beeps.

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 a marketing image GENERATED or an image prompt written — personal brand portraits, logos and monograms, campaign key visuals, day-to-day social graphics, editorial art, infographics, web hero mockups, and quote graphics. Reads brand identity from project context, composes an on-brand prompt, generates via gpt-image-2 when an API key exists, otherwise outputs paste-ready prompts for DALL-E 3, MidJourney, Leonardo, or Ideogram. Trigger on 'design an image', 'make me a logo', 'MidJourney prompt', 'key visual for the campaign', 'generate a graphic for this post', 'I need a visual and have no designer'. Not for — briefing a human designer on a static, see `42-image-brief-global`; a slide sequence, see `43-carousel-brief-global`; the brand rules themselves, see `46-brand-guideline-global`; scoring a finished design, see `47-design-review-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。

Writes or reviews lyrics with professional prosody, rhyme craft, and quality checks. Use when writing new lyrics, revising existing lyrics, or when the user says 'let's work on a track.'

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。