「pipelines」の検索結果

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。

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

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 Dagger — dagger CI/CD pipeline management. Covers pipeline-as-code configuration, module management, function execution, caching layers, container builds, and pipeline debugging. Use when managing Dagger pipelines, debugging function execution, inspecting modules, or optimizing container-based CI 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。

Use when working with Coveo — coveo enterprise search platform management including sources, indexes, query pipelines, machine learning models, usage analytics, and security providers. Covers indexing health, query performance, ML model status, content freshness, and license utilization.

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 Bitbucket Deep — bitbucket deep platform management covering repository inventory, Pipelines CI/CD monitoring, pull request analysis, branch permission auditing, deployment environment tracking, and workspace member management. Use when auditing repository configurations, investigating pipeline failures, reviewing branch restrictions, or managing workspace 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。

Use when working with Azure Devops — azure DevOps comprehensive management. Covers pipelines, boards, repositories, artifacts, test plans, work item tracking, and release management. Use when checking pipeline status, managing work items, investigating build failures, or auditing Azure DevOps project configurations.

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 Auth0 — auth0 identity platform management for tenant configuration, application setup, connection analysis, rule and action review, user management, and log inspection. Covers universal login, social connections, enterprise federation, and Auth0 Actions pipelines. Read this skill before any Auth0 operations — it enforces discovery-first patterns and strict read-only safety 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。

Use when working with Mongodb — mongoDB database analysis, performance tuning, query optimization, and health monitoring. Covers collection analysis, index recommendations, aggregation pipelines, replica set health, Atlas cluster management, and slow query investigation.

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 Tfsec — tfsec Terraform security scanning. Covers static analysis of Terraform code, custom rule creation, CI integration, severity filtering, module scanning, and remediation guidance. Use when scanning Terraform configurations for security issues, creating custom security rules, or integrating security checks into CI 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。

Use when working with Semgrep — semgrep static application security testing (SAST). Covers code scanning, custom rule creation, CI integration, autofix capabilities, multi-language support, and vulnerability triage. Use when scanning source code for security vulnerabilities, creating custom detection rules, or integrating SAST into CI 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。

Plan and run multi-agent video production 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。

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。

Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG 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。

MongoDB with Mongoose — schemas, models, aggregation pipelines, migrations, and Atlas connections. Use when designing collections, writing queries, or integrating MongoDB into Node.js/Next.js apps.

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。

Evaluate and improve AI-generated output with explicit rubrics, reflection loops, and stop conditions. Use when building self-critique workflows, evaluator-optimizer pipelines, or acceptance gates for code, docs, analysis, or plans.

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 SDK development guidance for Python pyservicemaker pipelines, video analytics, TensorRT integration, and streaming inference 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。

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。

Git operations, shell scripting, CI/CD pipelines, and terminal automation. Use for conventional commits, PowerShell/Bash scripting, configuring GitHub Actions, or automating development tooling 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。

Automate doc generation with JSDoc/TSDoc, linters, and pre-commit hooks. Use when setting up markdownlint, configuring doc linting pipelines, integrating JSDoc/TSDoc, or building automated documentation 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。

DevSecOps IA — Expert en intégration sécurité dans les pipelines CI/CD (SAST, DAST, SCA, container scanning, compliance automation)

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 en data engineering (ETL, Airflow, dbt, data lakes, streaming pipelines, data quality)

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 en pipelines CI/CD (GitHub Actions, GitLab CI, Jenkins, ArgoCD, progressive delivery)

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。

Migrate a .NET 10 project or solution to .NET 11 and resolve all breaking changes. This is a MIGRATION skill — use it when upgrading from .NET 10 to .NET 11, NOT for writing new programs. USE FOR: upgrading TargetFramework from net10.0 to net11.0, fixing build errors after updating the .NET 11 SDK, resolving source-breaking and behavioral changes in .NET 11 runtime, C# 15 compiler, and EF Core 11, adapting to updated minimum hardware requirements (x86-64-v2, Arm64 LSE), and updating CI/CD pipelines and Dockerfiles for .NET 11. DO NOT USE FOR: .NET Framework migrations, upgrading from .NET 9 or earlier, greenfield .NET 11 projects, or cosmetic modernization unrelated to the upgrade. NOTE: .NET 11 is in preview. Covers breaking changes through Preview 3.

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。

Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and 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。