「serving」の検索結果

Turn an authorized 2D logo into an approved visual treatment and animate a controlled brand reveal while preserving the mark.

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 draft video-ad variations from supplied performance evidence, preserving the distinction between observed data and creative hypotheses.

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。

Edit, extend, transition, and combine existing video while preserving an explicit parent asset and audio decision.

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 approved video clips, audio, captions, and timing decisions into an ordered, reviewable draft while preserving a reproducible timeline.

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。

Produce product-led video ad concepts and variants while preserving approved product details, claims, and platform constraints.

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。

Upscale and prepare a selected video parent for delivery while preserving provenance and checking that enhancement did not create new defects.

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。

Apply when introducing a new internal API while old callers still exist. Migrate callers and delete the old API in the same wave instead of preserving compatibility layers.

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 starting, stopping, or inspecting the dev stack for this Hydrolix Grafana datasource plugin — Grafana (with the plugin bind-mounted), ClickHouse, Keycloak (OAuth), and the on-demand playwright runner. Covers `docker compose up` semantics, the `dist/` prerequisite, serving plugin artifacts from an alternate folder (any path, live or frozen, via an ephemeral compose override), switching Grafana versions, hot-reload behaviour, delve attach, log streaming, OAuth/anonymous auth, and ClickHouse fixture access. Apply whenever a task needs the plugin running locally, needs to reset the stack, or needs to debug why Grafana won't come up.

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。

Semantically merge upstream kit changes while preserving project-specific values and recording sync state

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。

Bun runtime, package manager, bundler, and test runner. Use when running scripts with bun, managing packages, serving HTTP with Bun.serve, querying databases with Bun.sql/bun:sqlite/Bun.redis, shell scripting with $, using S3/file I/O, writing tests with bun:test, bundling or compiling to executable, or using any Bun-specific API (spawn, glob, semver, FFI, workers, plugins, HTMLRewriter).

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, edit, validate, and run Agent QA tests, suites, and hooks through MCP or CLI while preserving canonical IDs and schema contracts.

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 working with Baseten — baseten ML deployment platform management covering model inventory, deployment status, autoscaling configuration, inference call history, GPU allocation, environment management, and performance metrics. Use for comprehensive Baseten workspace assessment and ML serving optimization.

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, resize, crop, reformat, and optimize images on demand via Netlify Image CDN's /.netlify/images endpoint. Use when adding responsive images, generating thumbnails, converting formats (avif/webp/png), cropping to aspect ratios, tuning image quality, creating blurred placeholders, allowlisting remote image domains, serving user-uploaded images, or wiring framework image components (Next.js, Astro, Nuxt, Angular, Gatsby) to Netlify. Triggers on tasks like "optimize images", "add image thumbnails", "resize images on the fly", "serve images from an external domain", or "add blur placeholders".

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 to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.

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 and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.

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。

Simplifies and refines code for clarity, consistency, and maintainability while preserving all functionality. Use when asked to "simplify code", "clean up code", "refactor for clarity", "improve readability", or review recently modified code for elegance. Focuses on project-specific best practices.

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。

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

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。

Collect and verify Google Street View exterior references for a building reconstruction, preserving panorama identity, imagery dates, attribution and viewpoint separately from calibrated scan evidence.

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, read, and manage calendar events and reminders using EventKit and EventKitUI. Use when adding events to the user's calendar, creating reminders, setting recurrence rules, requesting calendar or reminders access, presenting event editors, choosing calendars, handling alarms, observing calendar changes, or working with EKEventStore, EKEvent, EKReminder, EKCalendar, EKRecurrenceRule, EKEventEditViewController, EKCalendarChooser, or EventKitUI views.

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。

Measure ad effectiveness with privacy-preserving attribution using AdAttributionKit. Use when registering ad impressions, handling attribution postbacks, updating conversion values, implementing re-engagement attribution, configuring publisher or advertiser apps, or replacing SKAdNetwork with AdAttributionKit for ad measurement.

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。

Discover and configure Bluetooth and Wi-Fi accessories using AccessorySetupKit. Use when presenting a privacy-preserving accessory picker, defining discovery descriptors for BLE or Wi-Fi devices, handling accessory session events, migrating from CoreBluetooth permission-based scanning, or setting up accessories without requiring broad Bluetooth permissions.

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。

Tones down visually aggressive or overstimulating designs, reducing intensity while preserving quality. Use when the user mentions too bold, too loud, overwhelming, aggressive, garish, or wants a calmer, more refined aesthetic.

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。

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

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。

Natural, identity-preserving portrait retouching with a local CLI and a Busabase-backed review app. Use when the user asks to 美颜, 修人像, 磨皮, 提亮肤色, portrait retouch, headshot cleanup, profile-photo polish, before/after comparison, or batch portrait enhancement. Default to local non-destructive processing, preserve facial structure and skin texture, and require explicit approval before replacing or publishing any 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。