922 件 ・ 関連度順
概要と使いどころ
Use when the user mentions tosutil, TOS object storage, bucket/object operations, batch upload or download, object metadata, TOS connectivity, or errors such as 403/network/argument failures. 围绕火山引擎对象存储 tosutil 生成与校验命令、规划桶/对象操作并诊断错误；当用户提到 tosutil、TOS 桶对象管理、批量上传下载或相关排障时调用。
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 encounters VolcEngine errors or needs local troubleshooting for OpenAPI, Python SDK, CLI, IAM, billing, compute, networking, storage, database, CDN, media, AI, security, or VKE cases.
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 Terraform/IaC for Volcengine resources only when the user explicitly chooses Terraform/IaC, already has a Terraform workflow/state, or confirms they need plan/diff/drift/destroy safety for VKE, managed databases/cache/storage, load balancers, domains/certificates, logging/monitoring, or team-managed infrastructure.
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。
Manage Volcengine's AI-native BaaS platform (Supabase edition / AIDAP / 火山引擎 AI 原生 BaaS 平台 Supabase 版) — a Volcengine-operated distribution that differs from official Supabase. Use when the user asks to create, inspect, or manage Volcengine Supabase or AIDAP resources — workspaces, branches, computes, SQL queries, schema changes, Auth, Realtime, Edge Functions, Storage buckets, frontend static-site hosting (Pages), API keys, connection info, or TypeScript type generation — or when a Volcengine deployment selects AIDAP as its database provider. Also trigger on Chinese prompts mentioning "火山引擎 Supabase" or "火山 Supabase". Operations run through the byted-supabase-cli command-line tool (installed via `npm i -g @byted-supabase/cli`; this is NOT the official `supabase` CLI). Do NOT use it for general database discussions, non-Supabase services (RDS MySQL, Redis), or pure client-side coding unrelated to Supabase backend 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。
Guidance for Tauri v2 stronghold plugin with encrypted storage and sensitive data handling.
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 deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization, GitOps pipelines, and multi-cluster 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。
Search, read, upload, organize, and share files and folders in the user's Dropbox cloud storage. Use to upload or download files, collect client uploads with file requests, inspect or create shared links, and create, copy, move, or delete content through Dropbox's official APIs.
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 cached contacts and calendar events from Muse storage. Delete Muse's local copy of either source without modifying paired devices.
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。
Audit manufacturing predictive maintenance systems for OPC-UA/MQTT sensor data pipelines, time-series storage retention, ML model lifecycle (training-serving skew, drift detection, retraining triggers), MTBF/MTTF/MTTR reliability calculations, Weibull survival 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。
High Availability control plane for Yuzu — the canonical entry point for any work on ADR-2002 (active-active server tier, gateway-fronted routing, Postgres-backed coordination seam, HA Postgres storage). Use when the user says "/ha", "/high-availability", "/ha-matrix", asks to plan or implement an HA workstream (WS-0…WS-14), asks "what's our HA gap" or "is it safe to run a second replica yet", asks to audit HA readiness, or starts work touching the coordination seam (leader election / fenced epochs / transactional outbox), gateway intra-cluster routing, shared `AgentRegistry` presence, PKI/CA HA, or the `deploy/docker/*ha*` / `scripts/ha/` surface. The skill bundles the two-axis model, the safe-to-scale gate, the delivery matrix (current-state + reviewers + status), the per-workstream workflow, and the load order for the routed reference docs.
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 agents through a 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage, MIGs, GKE, Cloud Run) to use as backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancers. - Actuating deployments via Infrastructure Manager or bash scripts, including IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).
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。
Diagnoses and resolves Google Cloud Filestore client mount failures, permission errors (EACCES), and network timeouts (ETIMEDOUT). Use when an NFS mount hangs or fails from a Compute Engine VM, GKE pod, Cloud Run service, or Vertex AI workload, when `mount.nfs` reports "Connection timed out" or "access denied by server", when checking whether VPC ingress firewall rules or `nfsExportOptions` allow a client IP, or when a previously working Filestore share suddenly stops mounting after an administrative change. Don't use for Cloud Storage (GCS) buckets, Persistent Disk, or Cloud NetApp Volumes, and don't use for Filestore capacity scaling or backup and export-policy auditing.
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。
Inspects, searches, and reads files and POSIX metadata on Google Cloud Filestore (NFS) instances without local NFS client packages or root privileges. Use when browsing Filestore shares, searching files, reading remote logs, or inspecting file attributes; don't use for Cloud Storage buckets, Cloud NetApp Volumes, Persistent Disks, or modifying/deleting files.
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。
Retrieve, query, and identify relevant Google Cloud Monitoring metric descriptors for a GCP service or resource (such as Compute Engine, Spanner, BigQuery, Cloud Run, Cloud SQL, Pub/Sub, Cloud Storage, etc.). Use when asked to find, list, search, or discover GCP metric types, names, kind/value schemas, or descriptors.
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。
Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. - Assessing the consequences of modifying, deleting, or pausing updates to a BigQuery asset. - Identifying downstream dependencies (tables, dashboards, processes) of a BigQuery asset. Don't use for: - General BigQuery querying or data analysis (use BigQuery-related tools instead). - Non-BigQuery assets (e.g., Cloud Storage files) unless they are part of the BigQuery lineage. - Creating or modifying lineage links directly.
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 data-retrieval best practices, tool selection guidance, and performant SQL query syntax for BigQuery telemetry across INFORMATION_SCHEMA, Cloud Monitoring, and the REST API. Use when the telemetry to fetch is already known, selecting telemetry tools, writing performant INFORMATION_SCHEMA queries, retrieving telemetry for diagnosing single-job performance bottlenecks, investigating slot contention, job concurrency and queue latency, analyzing reservation capacity, utilization and autoscaling saturation, or auditing capacity-based and on-demand compute and storage resource billable usage. Don't use for root-cause diagnosis or symptom troubleshooting when the cause is unknown (use bigquery-troubleshooting first), or for writing or optimizing business logic SQL (use bigquery-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。
Use when reviewing or refactoring code that pulls apart another object's private representation, such as raw limb/byte/slot access, slice constructors, or helper methods that expose internal storage. Guides agents to find representation envy and suggest moving behavior onto the object that owns the representation, using live-image Genie tools when working in Pharo.
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 cross-browser extensions with WXT — the modern framework for Chrome, Firefox, Safari, and Edge extensions. Use when someone asks to "build a browser extension", "Chrome extension with React", "WXT framework", "cross- browser extension", "manifest v3 extension", "build Firefox extension", or "browser extension with TypeScript". Covers content scripts, background workers, popup/options pages, storage, messaging, and publishing.
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 in batch cooking, meal planning, food storage, and efficient kitchen workflows
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。
Adaptive learning for moflo agents via ReasoningBank: trajectory storage, verdict judgment, memory distillation, consolidation, and MMR retrieval. Use when building agents that should improve from experience across runs.
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 non-binding follow-up action suggestions from lead summaries or lead lists. Use when users ask for next best actions, call list for hot leads, or follow-up draft plan without automatic execution. Recommended chain: summary-generator then action-suggester then supervisor approval. Do not use for parsing, storage, or autonomous action execution.
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。
Structured memory system for OpenClaw agents. Context death resilience (checkpoint/recover), structured storage, Obsidian-compatible markdown, local semantic search, and session transcript repair.
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。
Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services.
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。
Design asynchronous messaging patterns in Azure using Service Bus, Event Hubs, Event Grid, and Storage Queues. Use this skill when users ask for queueing, pub-sub, event streaming, retries, or decoupled system design. Covers delivery semantics, dead-lettering, idempotency, 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。