「pipe flow」の検索結果

Core ComfyUI knowledge covering workflow format, node types, pipeline patterns, and MCP tool usage

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。

Code generator skills that produce production-ready Swift code for common app components. Use when user wants to add logging, analytics, onboarding, review prompts, networking, authentication, paywalls, settings, persistence, error monitoring, CI/CD pipelines, localization, push notifications, deep linking, testing, accessibility, widgets, feature flags, app icons, image caching, pagination, HTTP caching, share cards, social export, subscription lifecycle, referral systems, watermarks, streak tracking, milestone celebrations, what's new screens, lapsed user re-engagement, usage insights, variable rewards, consent flows, account deletion, permission priming, force updates, state restoration, debug menus, offline queues, feedback forms, announcement banners, quick win sessions, Spotlight indexing, App Clips, screenshot automation, background processing, app extensions, data export, or SwiftUI preview sample data and variant matrices.

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。

End-to-end motion-design / animated-ad creation flow on Higgsfield via the MCP connector. Use when the user wants to create motion design, animate a logo, make a video from an image, build an animated ad or brand promo, turn a product into motion, or says 'make a motion', 'motion design', 'animate this', 'make a video from my logo', 'animated brand', 'motion graphics', 'brand motion', 'kinetic graphics', 'promo video', or 'ad video'. Drives a storyboard-first pipeline: brief → storyboard sheet (GPT Image 2) → video (Seedance 2.0) — an AI-generated pixel video clip. Distinct from higgsfield-motion (the named camera/motion preset library) and from higgsfield-vibe-motion (deterministic Remotion code with crisp text); use vibe-motion instead when the text/logo must stay perfectly crisp, editable, and deployable as code.

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。

公众号运营｜微信公众号｜公众号一条龙｜公众号全流程｜自媒体运营｜wechat automation｜content pipeline｜AIGC workflow — 公众号一条龙运营总控入口，选题→写稿→审稿→排版→配图→发布串联 8 个子 skill，单条指令完成整篇图文从 0 到上架。面向公众号小编、自媒体、品牌内容。触发词分层：**一条龙流程**「一条龙」「完整流程」「从头做」「从 0 到发布」；**新做新发**「帮我写篇公众号文章」「做一篇公众号文章」「我想发一篇」「帮我发一篇」「再来一篇」；**选题起点**「今天写什么好」「有什么好写的」「找个话题」「爆款选题」「热点选题」「起个爆款标题」；**策划起点**「内容日历」「系列策划」「专栏规划」「连载」；**流程恢复**「接着上次那篇」「继续昨天的」「继续上次的」「接着之前的进度」；**显式模型新写**「用 GPT 写一篇」「用 DeepSeek 写一篇」「把提纲写成文章」。子 skill（topics/writing/review/formatting/images/publish/sticker/assets）单独触发仅限对**已有产物**的修改场景（如"改标题""润色这段""排版""审稿""加封面""发布"）；新做/策划/多环节串联一律走本入口。

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。

Weekly, on a Friday, read only everywhere. Scores the week from the ledgers with a source path beside every number, replays the browser flows the other routines depend on, names one thing to kill and one thing to scale, and files both as cards. It sends only where you released the channel, spends only where you released it, never touches a credential, and never writes a number it did not count out of a named file this run.

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。

Dung khi mot CA NHAN muon len hinh bang AI thay vi tu quay — pipeline avatar AI: 3 tier cong cu, 4 workflow gom avatar don, dich da ngon ngu, san xuat hang loat va hybrid nguoi that cong AI; nhan anh reference de tao prompt avatar; thay mat, style, logo; ghep voice clone; tranh bi nen tang danh dau; cong bo AI theo Nghi dinh 147/2024 va QA 100 diem. Cong cu HeyGen, Synthesia, ElevenLabs, Captions, Vbee. Kich hoat khi user nhac 'tao avatar AI', 'video HeyGen', 'talking head AI', 'lam video ma ngai lo mat', 'batch video AI', 'dich video sang tieng Anh', 'prompt avatar'. Khong dung cho — clone giong cho podcast va audio thi dung skill 25-voice-clone-podcast; viet loi thoai video thi dung skill 04-script-video; anh tinh thi dung skill 30-thiet-ke-master.

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。

Phase 3 of the prd-taskmaster pipeline: smart mode selection and user handoff. Detects installed capabilities (superpowers, ralph-loop, task-master-ai, playwright, research providers), recommends ONE execution mode (A/B/C) with reasoned justification, appends the task-execution workflow to CLAUDE.md, surfaces a structured AskUserQuestion multi-option picker for user agency, and dispatches the chosen mode. Mode D (Atlas Fleet) is selectable only when detect_capabilities returns tier=premium (licensed atlas-launcher detected); otherwise it is a locked Atlas Pro teaser. Plan Mode is NOT used (spec section 13.5): AskUserQuestion is the sole user-agency mechanism. Declares HANDOFF complete so EXECUTE can follow.

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。

Set up CI/CD pipelines for Flutter apps. Use when configuring automated testing, build, or deployment workflows with GitHub Actions or Fastlane.

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。

Unified team skill for performance optimization. Coordinator orchestrates pipeline, workers are team-worker agents. Supports single/fan-out/independent parallel modes. Triggers on "team perf-opt".

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。

Unified team skill for code review. 3-role pipeline: scanner, reviewer, fixer. Triggers on team-review.

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。

Unified team skill for architecture optimization. Uses team-worker agent architecture with role directories for domain logic. Coordinator orchestrates pipeline, workers are team-worker agents. Triggers on "team arch-opt".

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。

Unified team skill for issue resolution. Uses team-worker agent architecture with role directories for domain logic. Coordinator orchestrates pipeline, workers are team-worker agents. Triggers on "team issue".

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。

将用户输入的整数加10并返回结果。当用户提到「流水线」关键词时并提供数字时使用，并且此方法是「流水线」系列技能之一，能与其他技能之间传递结果。

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。

将用户输入的数字乘以10并返回结果。当用户提到「流水线」关键词时并提供数字时使用，并且此方法是「流水线」系列技能之一，能与其他技能之间传递结果。

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。

将用户输入的整数减去5并返回结果。当用户提到「流水线」关键词时并提供数字时使用，并且此方法是「流水线」系列技能之一，能与其他技能之间传递结果。

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。

Orchestrator-only workflow for migrating/rewriting codebases with full TDD and agent delegation

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 Actions workflow templates, matrix builds, caching, and monorepo CI 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。

Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migrating from pandas to polars, or orchestrating multi-step transformations with testing and quality checks.

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。

Implementing multi-layer security scanning (container, SAST, DAST, SCA, secrets), SBOM generation, and risk-based vulnerability prioritization in CI/CD pipelines. Use when building DevSecOps workflows, ensuring compliance, or establishing security gates for container deployments.

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。

Implement applications using Google Cloud Platform (GCP) services. Use when building on GCP infrastructure, selecting compute/storage/database services, designing data analytics pipelines, implementing ML workflows, or architecting cloud-native applications with BigQuery, Cloud Run, GKE, Vertex AI, and other GCP 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。

Code-only motion design pipeline (no After Effects) for Raphaël / Howseen: launch films, showreels, product promos, LinkedIn/X videos, meme clips. Use when asked to make a motion design video, a promo/launch film, a showreel, "remake this video", a video from a prompt (e.g. "make a 15s motion graphics video…"), to change a video's music/SFX, or to prepare memes for posts. Covers the brief → beat map → stills → seek(t) HTML engine → Playwright render → ffmpeg → music/SFX → QA flow, plus asset sourcing (Mixkit, Pexels, Unsplash, svgl, 21st.dev) and every gotcha hit so far.

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。

Write, review, or modernize F# code in .NET repositories with functional-first design, algebraic data types, pattern matching, pipelines, async workflows, project ordering, and C# interop. USE FOR: F# .fs/.fsproj code; discriminated unions, records, options, results, pattern matching, computation expressions, or functional domain modeling; strongly typed AI-generated .NET code. DO NOT USE FOR: C# language modernization; FSI-only exploratory scripts with no project changes. INVOKES: inspect .fsproj file order and SDK settings, edit F# source and project files, and run dotnet build/test or dotnet fsi validation commands when changes are made.

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。

Automatically generate production-ready Skills for any software, API, CLI tool, library, workflow, or service. Use this skill whenever the user wants to create a skill from scratch for a target application, convert an existing tool into an agent-native skill, generate skills for multiple platforms (Claude Code, OpenClaw, Codex), or automate the full skill creation pipeline including analysis, design, implementation, testing, optimization, and multi-platform packaging. Also use when the user mentions "skill-anything", "generate a skill for", "make a skill from", "skillify", or wants to turn any software into an agent-ready skill. Even if they just say "create a skill for X" where X is any tool or API, this skill should trigger.

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。