「workflows」の検索結果

Digital art tools, techniques, and workflows for art education. Covers raster and vector workflows, digital painting, photo manipulation, generative and procedural art, 3D modeling and rendering, pixel art, the relationship between traditional skills and digital execution, and ethical considerations of AI-generated imagery. Use when working with digital tools, evaluating digital art, or bridging traditional art concepts into digital practice.

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 guide for building robust, secure, and efficient CI/CD pipelines using GitHub Actions. Use when the task involves `creating or editing GitHub Actions workflows`, `.github/workflows/*.yml`, `CI/CD pipelines`, `GitHub Actions best practices`, or `workflow 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。

Design and implement agentic AI workflows and patterns. Covers ReAct, planning agents, tool use, memory systems, and multi-agent orchestration. Use when building autonomous AI agents, implementing complex task automation, or designing intelligent workflow 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。

Comprehensive guide for building AI workflows, agents, and workforce systems with AgenticFlow. Use when designing workflows with various node types, configuring single agents, or orchestrating workforce collaboration 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。

AI agent workflow patterns including ReAct agents, multi-agent systems, loop control, tool orchestration, and autonomous agent architectures. Use when building AI agents, implementing workflows, creating autonomous systems, or when user mentions agents, workflows, ReAct, multi-step reasoning, loop control, agent orchestration, or autonomous AI.

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。

Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous 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。

Compose, orchestrate, and trace production multi-agent workflows with Microsoft Agent Framework.

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 ZCF to initialize, update, and standardize Claude Code or Codex environments with prompts, workflows, MCP services, API settings, and backups.

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 GitHub Agentic Workflows to let an agent triage issues, inspect CI failures, or deliver scheduled repository upkeep inside GitHub Actions with explicit workflow definitions and reviewable runs. This is for bounded, repeatable repository operations, not for listing GitHub as a general coding 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。

This ASE skill uses zizmor to audit GitHub Actions workflows and composite actions for security mistakes before they ship. An agent can scan local repos or remote GitHub repositories, flag risky permission scopes and unsafe workflow patterns, and return plain output, GitHub-native findings, or SARIF for follow-up 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。

Analyzes Argo Workflows DAG templates to identify parallelization opportunities. Uses the Argo Server API to fetch workflow execution history and critical path 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。

Orchestrates deployment pipelines using the Argo Workflows Engine API and Argo CD ApplicationSet controller. Implements progressive delivery with Argo Rollouts canary and blue-green 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。

Lints and validates Argo Workflows templates using the argo CLI and Argo Server REST API. Detects DAG dependency cycles, invalid artifact references, and parameter type mismatches across workflow 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。

Constructs Kubernetes-native workflow DAGs using Argo Workflows CRDs with configurable retry strategies, artifact passing via S3/MinIO, and template composition through WorkflowTemplates and ClusterWorkflowTemplates.

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。

An ASE skill built around ACF Extended, the WordPress enhancement suite for Advanced Custom Fields that adds field types, admin improvements, front-end forms, options pages, and developer tooling. It is a practical fit for agents working inside complex WordPress content models and custom field 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 Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and 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。

Build and refine TouchDesigner projects with tdmcp using context-first, visible, reversible 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。

Comprehensive guide for building robust, secure, and efficient CI/CD pipelines using GitHub Actions. Use when the task involves `creating or editing GitHub Actions workflows`, `.github/workflows/*.yml`, `CI/CD pipelines`, `GitHub Actions best practices`, or `workflow 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。

Build .NET AI agents and multi-agent workflows with Microsoft Agent Framework using the right agent type, threads, tools, workflows, hosting protocols, and enterprise guardrails.

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。

Check the status of running or recent SDLC delegated 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。

Cloudflare platform management via Wrangler CLI, Agents SDK (v0.13+), and Browser Rendering API. Deploy Pages, Workers, KV, R2, D1, Queues, Vectorize, Workflows, Hyperdrive. Build stateful AI agents with the full SDK stack — Agent, AIChatAgent, Think, Voice, sub-agents, fibers, HITL, scheduling, observability, Code Mode (Dynamic Worker sandboxes). Budget web scraping via cf_browser.py. Use when deploying to Cloudflare, managing CF infrastructure, configuring wrangler.toml/wrangler.jsonc, building AI agents or chat agents on Workers, adding voice, orchestrating sub-agents, or for cheap web scraping. Triggers: Cloudflare, wrangler, Pages, KV, R2, D1, Workers, Vectorize, Queues, Workflows, Hyperdrive, cf_browser, Browser Rendering, Agents SDK, Code Mode, codemode, MCP, Think, AIChatAgent, Voice agent, sub-agents, fibers, HITL, Dynamic Workers.

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。

.github/workflows/*.yml を自動解析し、CI で定義されたチェックをローカル実行する汎用スキル。 lint・fmt・test・build・audit 等に限定せず、ワークフローの run ステップを抽出して実行する。 エラーがあれば修正し、再実行して確認する。 Use when: CI を通したい、lint/test を実行したい、CI チェックしたい、 ワークフローをローカルで試したい。 Triggers: "CI", "ci-check", "lint", "test", "format", "fmt", "audit", "チェック", "検証", "CI 通して", "テスト実行", "ビルド確認"

Register trained models in MLflow Model Registry with version control, implement stage transitions (Staging, Production, Archived) with approval workflows, and manage model lineage with comprehensive metadata and deployment tracking. Use when promoting a trained model from experimentation to production, managing multiple model versions across development stages, implementing approval workflows for governance, rolling back to previous versions, or auditing model changes for compliance.

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。

Orchestrate end-to-end machine learning pipelines using Prefect or Airflow with DAG construction, task dependencies, retry logic, scheduling, monitoring, and integration with MLflow, DVC, and feature stores for production ML workflows. Use when automating multi-step ML workflows from data ingestion to deployment, scheduling periodic model retraining, coordinating distributed training tasks, or managing retry logic and failure recovery across pipeline stages.

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。