1,111 件 ・ 関連度順
概要と使いどころ
Develops full-stack Dart backends using the Serverpod framework with PostgreSQL, Redis, and Docker. Use when building type-safe API endpoints, defining YAML data models, configuring Serverpod auth, writing server-side tests, running database migrations, deploying to Docker/AWS/GCP, or using Serverpod Mini for database-less BFF proxy endpoints.
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 multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, and GCP. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
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 reusable Terraform modules for AWS, Azure, and GCP infrastructure following infrastructure-as-code best practices. Use when creating infrastructure modules, standardizing cloud provisioning, or implementing reusable IaC components.
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 asks to "perform cloud penetration testing", "assess Azure or AWS or GCP security", "enumerate cloud resources", "exploit cloud misconfiguratio...
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Cloud infrastructure and DevOps workflow covering AWS, Azure, GCP, Kubernetes, Terraform, CI/CD, monitoring, and cloud-native development.
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 cloud architect specializing in AWS/Azure/GCP multi-cloud infrastructure design, advanced IaC (Terraform/OpenTofu/CDK), FinOps cost optimization, and modern architectural patterns.
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。
Maintain IT asset inventory and configuration management database. Track hardware, software, and cloud resources. Use when managing IT assets.
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 generating cloud architecture diagrams as code — creating, modifying, or reviewing infrastructure diagrams using the Python Diagrams library. Covers AWS, Azure, GCP, Kubernetes, on-premises, and SaaS provider nodes. Generates PNG/SVG architecture diagrams from Python code with Graphviz rendering.
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 Cloud Custodian — cloud Custodian policy engine management. Covers policy authoring, dry-run execution, resource filtering, action enforcement, multi-cloud support (AWS/Azure/GCP), Lambda deployment, compliance reporting, and policy organization. Use when managing Cloud Custodian policies, auditing cloud resources, enforcing compliance rules, or reviewing policy execution results.
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。
Analyze Compute Engine VM, Cloud SQL, Persistent Disk, and serverless (Cloud Functions/Cloud Run) utilization to identify right-sizing opportunities. Uses Cloud Monitoring metrics with anti-hallucination rules for E2 shared-core instances, sole-tenant nodes, preemptible/spot VMs, SUD eligibility, peak vs average analysis, CUD-aware savings, and estimated monthly savings calculations.
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 Prowler — prowler cloud security assessment tool. Covers AWS, Azure, and GCP security posture assessment, CIS benchmark evaluation, compliance frameworks (PCI-DSS, HIPAA, SOC2), multi-account scanning, and remediation guidance. Use when assessing cloud security posture, running compliance audits, or investigating security findings across cloud providers.
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, execute, and document validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.
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。
NVIDIA DeepStream model-import guidance for bringing vision models from Hugging Face or NVIDIA NGC into DeepStream pipelines with export, TensorRT build, and benchmark steps.
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。
Validate GCI competition predictions and notebook outputs against expected schema, metric, and submission 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。
Refresh a safe, concise map of this GCI World 2026 workspace before deeper course, assignment, or dataset work.
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。
Symbolicate the .NET runtime frames in an Android tombstone file. Extracts BuildIds and PC offsets from the native backtrace, downloads debug symbols from the Microsoft symbol server, and runs llvm-symbolizer to produce function names with source file and line numbers. USE FOR triaging a .NET MAUI or Mono Android app crash from a tombstone, resolving native backtrace frames in libmonosgen-2.0.so or libcoreclr.so to .NET runtime source code, or investigating SIGABRT, SIGSEGV, or other native signals originating from the .NET runtime on Android. DO NOT USE FOR pure Java/Kotlin crashes, managed .NET exceptions that are already captured in logcat, or iOS crash logs. INVOKES Symbolicate-Tombstone.ps1 script, llvm-symbolizer, Microsoft symbol server.
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。
You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, and GCP.
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。
AWS, GCP, Azure data platforms, infrastructure as code, and cloud-native data solutions
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。
LLMs, prompt engineering, RAG systems, LangChain, and AI application development
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Initialize, update, and visualize codebase or personal knowledge wikis using LangChain OpenWiki. Enforces OKF v0.2, Grounded Claims, interactive visualizer graph, and MCP page-job lifecycle.
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Use when working on any Java or JVM project: plain Java, libraries, CLI tools, Maven/Gradle builds, Spring Boot, Jakarta EE, MyBatis/MyBatis-Plus, JPA/Hibernate, Lombok, Java tests, Java code review, API design, exception handling, security review, refactoring, dependencies, Java version upgrades, javax/jakarta migrations, or JVM runtime troubleshooting such as GC, OOM, thread dumps, deadlocks, high CPU, and performance issues.
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Use when working with iOS/macOS Keychain Services (SecItem queries, kSecClass, OSStatus errors), biometric authentication (LAContext, Face ID, Touch ID), CryptoKit (AES-GCM, ChaChaPoly, ECDSA, ECDH, HPKE, ML-KEM), Secure Enclave, secure credential storage (OAuth tokens, API keys), certificate pinning (SecTrust, SPKI), keychain sharing across apps/extensions, migrating secrets from UserDefaults or plists, or OWASP MASVS/MASTG mobile compliance on Apple platforms.
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。
Bridges UIKit and SwiftUI by wrapping UIKit views and view controllers in SwiftUI with UIViewRepresentable and UIViewControllerRepresentable, embedding SwiftUI in UIKit with UIHostingController, and coordinating delegate callbacks. Use when integrating camera previews, map views, mail compose, document scanners, PDF renderers, text views with attributed text, or other UIKit-only or third-party UIKit SDK surfaces into a SwiftUI app, or when migrating a UIKit app to SwiftUI incrementally.
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。
Perform cryptographic operations using Apple CryptoKit. Use when hashing data with SHA256/SHA384/SHA512, generating HMAC authentication codes, encrypting with AES-GCM or ChaChaPoly, signing with P256/P384/P521/Curve25519 keys, performing ECDH key agreement, storing keys in the Secure Enclave, or migrating from CommonCrypto to CryptoKit.
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。