「alb」の検索結果

Places album art files in the correct audio and content directory locations. Use when the user has generated or downloaded album artwork that needs to be saved.

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。

Renames an album or track, updating slugs, titles, and all mirrored paths. Use when the user wants to rename an album or 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。

Autonomous multi-pass lyric refinement for tightening, cohesion, and album unity. Use after lyrics are written to polish a track or entire album through iterative passes.

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。

Provides interactive guided album creation for new users. Use when the user is new to the plugin or asks for a walkthrough of the album creation process.

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。

Coordinates album release including QA, distribution prep, and platform uploads. Use when mastering and album art are complete and the user is ready to release.

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。

Provides AWS CloudFormation patterns for ECS clusters, task definitions, services, container definitions, auto scaling, blue/green deployments, CodeDeploy integration, ALB integration, service discovery, monitoring, logging, template structure, parameters, outputs, and cross-stack references. Use when creating ECS clusters with CloudFormation, configuring Fargate and EC2 launch types, implementing blue/green deployments, managing auto scaling, integrating with ALB and NLB, and implementing ECS 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, debug, serialize, and integrate Albumentations 2.x augmentation pipelines for images, masks, bboxes, keypoints, volumes, and PyTorch-style datasets.

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。

Applies the epidemiological reasoning and population-health frameworks of Albert Hofman (Harvard epidemiologist, Rotterdam Study). Trigger this skill whenever you are analyzing public health strategies, preventive medicine, cohort study design, cardiovascular or neurodegenerative disease risks, or healthy aging. Use it when evaluating whether to use population-wide interventions versus individual screening, assessing risk factors in elderly populations, or tracing adult chronic diseases back to early-life or fetal origins.

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。

Burn Red Book audio CDs or MP3 data CDs on macOS via cdrdao, sourcing from Hoodrat HDD or local files. Audio CDs carry CD-Text from ID3 tags; MP3 discs use ISO9660+Joliet (~700 MB). Handles full-album burns and cherry-picked playlists. Triggers on 'burn CD', 'burn album', 'make audio CD', 'mixtape disc', 'soundtrack for the car'.

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。

Four-stage alchemical code transmutation — nigredo (decomposition), albedo (purification), citrinitas (illumination), rubedo (synthesis) — with meditate and heal checkpoints between stages. Transforms tangled or legacy code into optimized, well-structured output through systematic material analysis. Use when transforming legacy code into modern equivalents, refactoring deeply tangled modules where incremental fixes keep failing, converting a codebase between paradigms, or when simpler refactoring approaches have stalled and a full-cycle transformation is needed.

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 wall of album covers, an image wall, a covers grid, or any square art drifting slowly in the background of a site. Includes collecting their saved albums from Spotify and building the wall from them. The wall goes behind whatever front the site already has; a frosted panel is the default when the site has none.

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。

Uses AWS Athena to query CloudTrail, VPC Flow Logs, S3 access logs, and ALB logs for forensic investigation. Covers CREATE TABLE DDL with partition projection, forensic SQL queries for Tespit etme unauthorized access, data exfiltration, lateral movement, and privilege escalation. Use investigating yaparken AWS security incidents or building cloud-native forensic workflows at scale.

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。

Arquitetura e diagnóstico AWS — VPC, EC2, ECS, EKS, ALB, NLB, RDS, ElastiCache, S3, CloudFront, Route53, IAM, WAF, GuardDuty. Use quando o usuário disser "AWS", "VPC", "ALB", "RDS", "revisar a arquitetura", "Well-Architected", "subnet", "security group", "IAM", ou citar qualquer serviço AWS. Leitura livre; qualquer mudança passa pelo portão de confirmação.

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。

Spotify Now Playing-style card with album art, progress bar, and playback controls, suited to video overlays or personal homepages.

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。

Make sure to use this skill whenever the user mentions anything related to Danish job listings, job search in Denmark, finding work in Denmark, or job vacancies on Jobdanmark — even if they don't explicitly mention jobdanmark.dk. Also invoke this skill for questions about specific Danish job categories, municipalities, job types, or salaries in a job-search context. Trigger phrases include: danish jobs, jobs in denmark, find job denmark, job search denmark, danish job listings, jobdanmark, job opslag, find job, jobsøgning, ledige stillinger, stillingsopslag, job i Danmark, fuldtidsjob, deltidsjob, studiejob, praktikplads, elev, fleksjob, IT job denmark, sygeplejersker job, håndværker job, ingeniør job, pædagog job, kontor job, leder job, salg job, hotel job, kirke job, job aarhus, job københavn, job odense, job aalborg, job sjælland, job jylland, job fyn, jobkategorier denmark, ledige job, ansøgningsfrist, søg job, job opslaget, jobopslag, danish vacancies, work in denmark, employment denmark, job denmark, jobs near me denmark, apprentice denmark, internship denmark, part-time denmark, full-time denmark.

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。

Make sure to use this skill whenever the user wants to search for jobs in Denmark, find Danish job listings, look up a specific job posting, or asks anything about the Danish job market — even if they don't mention jobindex.dk explicitly. Invoke this skill for questions about open positions, job vacancies, hiring in Denmark, job opportunities in Danish cities or sectors, or when the user wants to find work in Denmark. Also trigger for phrases like "find me a job", "are there any jobs for X in Copenhagen", or "what jobs are available in Aarhus" when the context is Denmark. Trigger phrases include: jobindex, jobsøgning, job i Danmark, ledige stillinger, job opslag, find job, stillingopslag, jobannonce, job vacancy denmark, danish jobs, jobs in denmark, job search denmark, work in denmark, find work denmark, IT jobs denmark, engineer jobs denmark, developer jobs copenhagen, marketing jobs aarhus, jobs aarhus, jobs copenhagen, jobs odense, jobs aalborg, job openings denmark, hiring denmark, job listings denmark, python jobs denmark, grafisk designer job, data engineer job, softwareudvikler job, full stack developer job danmark.

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。

Language-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k sentences/sec), lightweight (6MB memory), deterministic vocabulary. Used by T5, ALBERT, XLNet, mBART. Train on raw text without pre-tokenization. Use when you need multilingual support, CJK languages, or reproducible tokenization.

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。

Maps intelligence for local SEO: geo-grid rank tracking, GBP profile auditing via API, review intelligence across Google/Tripadvisor/Trustpilot, cross-platform NAP verification, competitor radius mapping, and LocalBusiness schema generation. Three tiers: free (Overpass + Geoapify), DataForSEO, and DataForSEO + Google. Use when user says "maps", "geo-grid", "rank tracking", "GBP audit", "review velocity", "competitor radius", or "SoLV".

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。

Language-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k sentences/sec), lightweight (6MB memory), deterministic vocabulary. Used by T5, ALBERT, XLNet, mBART. Train on raw text without pre-tokenization. Use when you need multilingual support, CJK languages, or reproducible tokenization.

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。

Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.

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 hyperrealistic PBR metal in Three.js: steel, brass, gold, copper and iron as true conductors (metalness 1, measured F0 tint, no albedo) with roughness-varied finishes (polished, brushed anisotropic, aged with patina and worn edges) lit by a dark HDR studio of real bright window cards prefiltered with PMREM. Use when metal looks like grey plastic, a dull blur, or a black hole; when blades, tools, rings, ingots, hardware or product metal need reflections with edges and structure; or when a finish needs scratches, streaks, fingerprints and bevels that catch light.

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。

Helps DevOps engineers configure mirrord Operator's Kafka queue splitting feature end-to-end. Generates the MirrordSplitConfig and MirrordPropertyList Kubernetes CRD YAMLs (the current resources; MirrordKafkaTopicsConsumer + MirrordKafkaClientConfig are deprecated but still supported), the matching mirrord.json split_queues section with message_filter and jq_filter, and Helm value guidance. Use this skill whenever the user mentions Kafka splitting with mirrord, MirrordSplitConfig, MirrordPropertyList, MirrordKafkaClientConfig, MirrordKafkaTopicsConsumer, Kafka queue/topic splitting, configuring mirrord with Kafka, Kafka Streams splitting, MSK IAM auth, or troubleshooting Kafka splitting sessions. Also trigger on split_queues with queue_type Kafka, or connecting mirrord to a Kafka cluster. This is a Team/Enterprise feature of mirrord.

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。

Help users install and configure the mirrord Operator for team/enterprise environments. Use when users ask about operator setup, Helm installation, cloud API key or license configuration, air-gapped/offline licensing, enabling features (queue splitting, DB branching, preview environments, multi-cluster), internal registries, OpenShift/GKE Autopilot, RBAC, or multi-user mirrord deployments. Also use when an AI agent hits a Team or Enterprise feature on a cluster with no license and needs to offer the user a trial (agent-started trial; the trial is Enterprise tier).

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。

Guide users from zero to their first working mirrord session — check system requirements, install mirrord via CLI, VS Code, or IntelliJ, run a first session against a Kubernetes target, and verify the connection. Use when a user is new to mirrord, wants to install it, needs help running their first session, or wants to debug or test a local process against their Kubernetes cluster.

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。