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概要と使いどころ
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。
Entry point for refreshing the DH workflow graph. Use when skills, agents, Mermaid flowcharts, MCP tools, or artifact flows change and docs/dh-workflow-graph.json must remain current.
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 the user wants a last30days-style pre-research pass in Deepline: discover the critical public, private, CRM, workflow, social, and web data sources for a research/enrichment job; compare provider coverage; estimate Deepline credit cost; recommend the source plan before building or running the workflow; or build custom language/messaging from buyer, competitor, community, and CRM evidence. Triggers: pre-research, source discovery, provider strategy, research data sources, ScrapeCreators, X/Twitter data, Reddit comments, public and private datasets, CRM data, workflow data, custom language, messaging language, pain language.
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。
Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development 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。
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。
Build multi-agent AI workflows with orchestration, tool use, and state management
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。
Guide plan → instrument → execute → validate with explicit checkpoints and questions. Use for ambiguous tasks or when enforcing a consistent agent workflow.
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。
Generate a new agent tool skill, written in the style of ASE skills, which orchestrates a workflow of sequential actions, parallel actions, sub-agent calls, and skill calls. Use when the user wants to "generate a skill", create a "workflow", "orchestrate" or "chain" multiple ASE skills, or automate a recurring multi-step procedure.
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 a plug-in-ready SDR operator package for sales development and outbound pipeline work: ICP definition, compliant lead-source plan, enrichment/research workflow, account scoring, outbound assets, CRM handoff, reply triage, meeting prep, approval gates, and loop memory. Use when "SDR", "sales development", "outbound SDR", "operator room", "lead gen pipeline", "prospecting pipeline", "ICP targeting", "Apify", "RapidAPI", "Clay", "Apollo", "agentic SDR workflow", "sales operating loop", "sales dashboard handoff", or any request to package outbound sales workflows that can later connect to data tools, CRMs, or operator surfaces.
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。
Inspect n8n nodes and templates, generate typed workflow code, and sync automations through Git-friendly files instead of hand-editing workflow JSON.
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。
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。
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。
Activepieces is an open-source, self-hostable workflow automation platform with 200+ integrations. It provides a visual builder for creating automated workflows and exposes all its connectors as MCP servers for AI agent use.
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 custom AI agents in Claude Code from a user's problem statement. This skill analyzes the user's use case, asks smart clarifying questions, researches the internet for similar agents (GitHub repos, blogs, Claude Code community patterns), and then architects and builds production-ready Claude Code agents — including subagents, skills, hooks, slash commands, MCP integrations, and CLAUDE.md configuration. Use this skill whenever the user wants to create an agent, build an automation workflow, set up a Claude Code subagent, design a multi-agent system, or says things like 'build me an agent for...', 'automate this with Claude Code', 'I want a subagent that...', 'help me create a workflow', 'set up an agent pipeline', or any variation of wanting Claude Code to do something specialized. Also trigger when the user mentions agent architecture, agent SDK, agentic workflows, or task delegation in Claude Code — even if they don't use the word 'agent' explicitly.
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。
Workflow recovery protocol for resuming workflows after context loss, session interruption, or errors. Handles state reconstruction, artifact recovery, and seamless workflow continuation.
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。
Install Archon, build the sdlc-worker Docker images, and configure SDLC workflows. Run once after installing the sdlc-workflows plugin.
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。
Install and configure the putior R package for workflow visualization. Covers CRAN and GitHub installation, optional dependencies (mcptools, ellmer, shiny, shinyAce, logger, plumber2), and verification of the complete annotation-to-diagram pipeline. Use when setting up putior for the first time, preparing a machine for workflow visualization tasks, when a downstream skill requires putior to be installed, or restoring an environment after an R version upgrade or renv wipe.
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。
Generate themed Mermaid flowchart diagrams from putior workflow data. Covers theme selection (9 themes including 4 colorblind-safe), output modes (console, file, clipboard, raw), interactive features (clickable nodes, source info), and embedding in README, Quarto, and R Markdown. Use after annotating source files and ready to produce a visual diagram, when regenerating a diagram after workflow changes, or when switching themes or output formats for different audiences.
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 an arbitrary codebase to auto-detect workflows, data pipelines, and file dependencies using putior's put_auto() engine. Produces an annotation plan that maps detected I/O patterns to source files across 30+ supported languages with 902 auto-detection patterns. Use when onboarding onto an unfamiliar codebase to understand data flow, starting putior integration in a project without existing annotations, auditing a project's data pipeline before documentation, or preparing an annotation plan before running annotate-source-files.
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。
Add PUT workflow annotations to source files using the correct language-specific comment prefix. Covers annotation syntax, skeleton generation via put_generate(), multiline annotations, .internal variables, and validation. Supports 30+ languages with automatic comment prefix detection. Use after analyzing a codebase and having an annotation plan, when adding workflow documentation to new or existing source files, or when documenting data pipelines, ETL processes, or multi-step computations.
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。
React Native project structure, Expo vs bare workflow detection, app.json/app.config.js patterns, asset handling, fonts, styling approaches, hot-reload-friendly idioms. Use this skill to: - Detect Expo (managed/dev-client/EAS/ejected) vs bare RN workflow. - Pick correct project layout for each workflow. - Configure app.json / app.config.js with bundle ID, splash, icons, deep link schemes. - Handle assets, fonts, images correctly. - Pick a styling approach (StyleSheet / NativeWind / restyle / styled-components). Do NOT use this skill for: - Platform-specific branching (see rn-platform-specific). - Navigation (see rn-navigation). - Storage (see rn-state-and-storage). - Testing (see rn-testing).
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。