415 件 ・ 関連度順
概要と使いどころ
Plan accessibility testing — assistive technologies, participant criteria, WCAG coverage, and session protocol. Use when scheduling testing with real AT users. Not for evaluating a design yourself — use `accessibility-audit` (design-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。
Set up recurring or scheduled work — anything the user wants run on a schedule, repeatedly, or at a future time ("every morning", "each weekday at 9am", "daily digest", "weekly report", "remind me", "run this on a cron"). Teaches how to author a durable Vexa Scheduler routine that survives restarts. Use this instead of any OS cron job, system timer, or session-only reminder.
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。
Creates and automates custom image builds with EC2 Image Builder - Linux, Windows, and macOS AMIs, and container images to ECR. Covers the build IAM role, Amazon-managed and custom components, image recipes, infrastructure and distribution configuration (launch templates, SSM parameters, other Regions), one-off builds, recurring scheduled pipelines for golden AMI automation and OS patching, custom image workflows, and diagnosing failed builds. Applies when creating, automating, or scheduling AMI or container image builds with Image Builder, or when debugging a failed build. Not for launching instances from existing AMIs, AMI lifecycle/retirement, or general EC2 fleet management.
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。
Authors and deploys MWAA workflow artifacts: Python Airflow DAGs for provisioned environments or YAML workflow files for Serverless. Covers operator selection, timeout design, retry strategy, scheduling, failure notifications, idempotency, and MWAA Serverless schema compliance. Deploys the artifact (S3 DAG upload or Serverless CreateWorkflow/UpdateWorkflow), creates an environment inline when approved, and redeploys fixes, then optionally hands off to testing-mwaa-workflow. Triggers on: create a DAG, write a pipeline, build a workflow, orchestrate tasks, Airflow DAG, data pipeline, schedule a job, deploy a DAG, deploy a workflow, YAML workflow. Not applicable to converting or migrating existing DAGs between provisioned and serverless (conversion is out of scope), running or smoke-testing a deployed workflow (handled by testing-mwaa-workflow) or diagnosing a failed run (handled by debugging-mwaa-workflow).
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。
Deploy Apify Actors and integrate scraping into external applications. Use when deploying an Actor to the platform, integrating Actor results into a web app (Next.js, Express), wiring webhooks, or scheduling scraping pipelines. Trigger with "deploy apify actor", "apify Vercel integration", "apify production deploy", "integrate apify results", "apify API endpoint".
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。
Production readiness checklist for Apify Actor deployments. Use when deploying an Actor to production, preparing for launch, or validating Actor configuration, scheduling, monitoring, and rollback before going live. Trigger with "apify production", "deploy actor to prod", "apify go-live", "apify launch checklist", "actor production ready".
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 editorial calendars for blogs with topic clusters, publishing schedules, material-change reviews, update plans, seasonal opportunities, content mix formula, template integration, and distribution scheduling. Plans monthly or quarterly calendars around reader needs, evidence changes, and sustainable publishing capacity. Use when user says "editorial calendar", "content calendar", "blog calendar", "publishing schedule", "blog plan", "content plan", "what should I write".
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 editorial calendars for blogs with topic clusters, publishing schedules, content decay detection, freshness update plans, seasonal opportunities, content mix formula, template integration, and distribution scheduling. Plans monthly or quarterly calendars optimized for SEO topic authority and freshness signals based on content priority. Use when user says "editorial calendar", "content calendar", "blog calendar", "publishing schedule", "blog plan", "content plan", "what should I write".
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。
Plans and delivers a single project — scope, estimation, scheduling, critical path, tracking, and recovering when it slips. Use this to plan a project, build or challenge a schedule, estimate credibly, track progress meaningfully, or recover a project that is late.
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。
Automate Google Calendar events, scheduling, availability checks, and attendee management via Rube MCP (Composio). Create events, find free slots, manage attendees, and list calendars programmatically.
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。
This skill should be considered when you need to repair an infeasible or non-optimal flexible job scheduling planning schedule into a downtime-feasible, precedence-feasible one while keep no worse policy budget.
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。
Optimize workload distribution across workers, processes, or nodes for efficient parallel execution. Use when asked to balance work distribution, improve parallel efficiency, reduce stragglers, implement load balancing, or optimize task scheduling. Covers static/dynamic partitioning, work stealing, and adaptive load balancing 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。
SCIP optimization with PySCIPOpt. Use when facing an optimization problem with an objective, hard constraints, soft penalties, integer decisions, routing, assignment, scheduling, allocation, packing, capacity, inventory, or service-level rules. Prefer modeling and solving the problem with PySCIPOpt when it is available.
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。
Choose placements that preserve useful residual capacity. Use for bin packing, GPU sharing, accelerator placement, and multi-resource scheduling where stranded capacity hurts future fit.
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。
Parse scheduling constraints from a email text.
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 Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch 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。
Write calm, businesslike co-parenting messages that keep the focus on the kids and stay out of the old conflict — for scheduling, expenses, decisions, and hard topics. Use when asked to write a message to my co-parent, respond to my ex about the kids, co-parenting communication help, or how to reply without a fight. Produces a message drafted in a neutral, child-centered tone (the 'BIFF'-style brief/informative/friendly/firm approach), the bait removed, a clear ask or answer, and a note on documentation — steering away from anything that escalates. Not legal advice.
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 master their personal output by shifting from reactive scheduling to intentional energy management, internal trigger mastery, and proactive boundary setting.
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。
Read and write Mastodon: verify the account, list own posts and followers, publish toots with native scheduling, upload media. Trigger phrases: mastodon, toot, post to mastodon, fediverse.
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 update OMA skills in the SSL-lite human-readable format. Use when adding a new `.agents/skills/{skill-name}/SKILL.md`, converting an existing skill to the standardized Scheduling / Structural Flow / Logical Operations / References structure, or validating whether a skill has enough routing, execution, resource, and safety detail.
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。
Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.
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 reactive/event-driven C# with R3 (Cysharp's modern reimplementation of Reactive Extensions). Covers the Observable<T>/Observer<T> model, the OnErrorResume error contract, async dispatch with AwaitOperation, Task/IAsyncEnumerable integration, TimeProvider/FrameProvider scheduling, the concurrency contract, and how R3 differs from System.Reactive (Rx.NET).
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 alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda scheduling, soft-core potentials, MBAR/BAR analysis, cycle-closure validation, and protocol-appropriate enhanced sampling. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.
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。
Query grid electricity forecasts and submit load events using EnergyKit to help users optimize home electricity usage. Use when building smart home apps, EV charger controls, HVAC scheduling, or energy management dashboards that guide users to use power during cleaner or cheaper grid periods.
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。