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概要と使いどころ
Use this skill only for Volcengine Redis cloud resource operations, including querying, inspecting, creating, or managing Volcengine Redis instances and related cloud resources. Trigger it when the user mentions Volcengine Redis, Volcengine Redis instances, Volcengine Redis inventory/detail lookup, Volcengine Redis operational metadata, or Volcengine Redis MCP/OpenAPI access.
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。
Viral video replication tool that supports copying popular video structures, scripts, and styles to generate similar content. Use this skill when users mention "viral replication, viral cloning, copy video, clone video, similar video" or express the desire to create content similar to a popular video.
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, designing, or modifying Java enterprise systems that expose, exchange, store, process, export, or port data across users, businesses, connected products, cloud providers, APIs, event streams, AI data pipelines, data spaces, or SaaS platforms and need EU Data Act engineering controls. This should trigger for requests such as Review a Java platform for EU Data Act controls; Design data access and portability evidence; Add data-sharing request workflows, export formats, interoperability, metadata, audit logs, cloud-switching support, non-personal data safeguards, or trade-secret handoffs; Assess Data Act engineering readiness before production release. Part of Plinth Toolkit
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, designing, or modifying Java enterprise systems that may support EU Market Abuse Regulation concerns, market surveillance, suspicious order and transaction reports, insider dealing controls, unlawful disclosure controls, market manipulation detection, inside information disclosure workflows, insider-list evidence, PDMR transaction notifications, alert explainability, model or rule provenance, reviewer decisions, or compliance escalation. This should trigger for requests such as Review a Java trading surveillance system for MAR controls; Design suspicious order and transaction monitoring evidence; Add alert explainability and reviewer-decision audit trails; Assess AI-assisted market-abuse detection before production release. Part of Plinth Toolkit
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。
Builds a role scorecard, interview loop, sourcing plan, reference-check guide and close plan for a hire, and grades an existing job description or loop. Use when you say 'I need to hire a PM', 'write a job description', 'interview questions', 'how do I run references', 'first sales hire', 'first marketer', 'head of product search', 'scorecard' or 'how do I close a candidate'. Draws on 210 Lenny's Podcast guests including Adam Ward, Keith Rabois and Lauren Ipsen.
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 used when working with Firebase projects, including initializing projects, adding Cloud Functions or Firestore collections, debugging emulator issues, or reviewing Firebase code. Triggers on "firebase", "firestore", "cloud functions", "emulator", "firebase auth", "deploy to firebase", "firestore rules".
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。
Translate technical security work into the language of non-security audiences — board, executives, engineering, customer success, customers, legal, procurement, sales. Covers incident communication, post-mortem narrative, audit-findings-for-stakeholders, risk justification, security spend justification, and customer-facing breach disclosure. Use when the user mentions 'security comms,' 'communicate this finding,' 'explain to my boss,' 'board update,' 'executive summary,' 'incident communication,' 'breach notification,' 'customer disclosure,' 'security memo,' 'post-mortem narrative,' 'risk justification,' 'why this matters to the business,' 'translate this finding,' 'stakeholder update,' or has technical security work that needs to land with a non-security audience.
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。
Close out a change without the deep review loop: stage, simplify code and docs, run the project's checks, smoke test, update the changelog, self-improve, and ship. Use when the user asks to "quick finalize", "quickly finalize", "finalize quickly", "light finalize", "wrap this up quickly", "close this out without the full review", or "ship this without the deep pass".
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。
Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
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 CloudBase document database Web SDK to query, create, update, and delete data. Supports complex queries, pagination, aggregation, and geolocation queries.
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 cloud costs through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.
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 attacking AWS/Azure/GCP cloud — IAM/identity privilege escalation, IMDS/metadata SSRF, Entra device-code & PRT theft, GCP impersonation chains, Kubernetes/container escape, IaC/CI-CD federation abuse
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。
File contributor or agent papercuts as GitHub issues labeled friction, or investigate those issues as the daily friction-log Cloud Agent. Use when you hit repo friction, when asked to log friction, or when spawned to resolve open friction issues.
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 operating Inngest API resources from the terminal with `npx inngest-cli@latest api`: Cloud/local run debugging, event-run lookup, function traces, function invocation, app syncs, webhooks, environments, keys, account checks, and Insights queries. Provides prescriptive command routing for agents: which CLI command to run for a run ID, event ID, app ID, function ID, Cloud environment, API key, missing ID, or potentially mutating operation. Use `inngest-cli` for dev server setup/general CLI workflows and `inngest-api` only when raw REST API v2 docs or OpenAPI fallback are 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。
Dataflow workflow engine for scalable bioinformatics pipelines. Defines processes (containerized tasks) connected by channels; runs local, HPC (SLURM/SGE), cloud (AWS/GCP/Azure), or Kubernetes via a single config change. Powers nf-core. Use Snakemake for rule-based Python workflows; use Nextflow for containerized, cloud-native, and nf-core pipelines.
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 best practices for robot perception systems covering cameras, LiDARs, depth sensors, IMUs, and multi-sensor setups. Use this skill when working with RGB image processing, depth maps, point clouds, sensor calibration (intrinsic, extrinsic, hand-eye), object detection, semantic segmentation, 3D reconstruction, visual servoing, or perception pipeline optimization. Trigger whenever the user mentions OpenCV, Open3D, PCL, RealSense, ZED, OAK-D, camera calibration, AprilTags, ArUco markers, stereo vision, RGBD, point cloud filtering, ICP registration, coordinate transforms, camera intrinsics, distortion correction, image undistortion, sensor streaming, frame synchronization, or any computer vision task in a robotics context. Also covers multi-camera rigs, time synchronization across sensors, perception latency budgets, and production deployment of perception pipelines.
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 used when the user needs to perform year-end closing adjustments (決算整理), review financial statements (決算書), compute depreciation, or review their trial balance. Trigger phrases include: "決算", "決算整理", "決算書を作る", "減価償却", "試算表", "残高試算表", "損益計算書", "貸借対照表", "BS", "PL", "期末処理", "棚卸し", "未払計上", "前払処理".
Provides AWS CloudFormation patterns for Amazon Bedrock resources including agents, knowledge bases, data sources, guardrails, prompts, flows, and inference profiles. Use when creating Bedrock agents with action groups, implementing RAG with knowledge bases, configuring vector stores, setting up content moderation guardrails, managing prompts, orchestrating workflows with flows, and configuring inference profiles for model 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。
Provides AWS CloudFormation patterns for security infrastructure including KMS encryption, Secrets Manager, IAM security, VPC security, ACM certificates, parameter security, outputs, and secure cross-stack references. Use when implementing security best practices, encrypting data, managing secrets, applying least privilege IAM policies, securing VPC configurations, managing TLS/SSL certificates, and implementing defense in depth 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。
Provides AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.
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 EC2 instances, Security Groups, IAM roles, and load balancers. Use when creating EC2 instances, SPOT instances, Security Groups, IAM roles for EC2, Application Load Balancers (ALB), Target Groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.
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 Amazon S3. Use when creating S3 buckets, policies, versioning, lifecycle rules, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.
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 SonarQube and SonarCloud integration patterns via the Model Context Protocol (MCP) server. Enables quality gate monitoring, issue discovery and triaging, pre-push code analysis, and rule education directly in the agent workflow. Use when the user wants to check quality gates, search for Sonar issues, analyze code snippets before committing, or understand SonarQube rules. Triggers on "sonarqube", "sonarcloud", "quality gate", "sonar issues", "analyze with sonar", "check sonar", "sonar rule", "pre-push 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。
Provides AWS CloudFormation patterns for Auto Scaling including EC2, ECS, and Lambda. Use when creating Auto Scaling groups, launch configurations, launch templates, scaling policies, lifecycle hooks, and predictive scaling. Covers template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and best practices for high availability and cost 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。