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概要と使いどころ
ActiveCampaign Automation via Rube MCP workflow skill. Use this skill when the user needs Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," "lifecycle emails," "trigger-based emails," "email funnel," "email workflow," "what emails should I send," "welcome series," or "email cadence." Use this for any multi-email automated flow. For cold outreach emails, see cold-email. For in-app onboarding, see onboarding.
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。
Automated iterative agent runner for spec-based development in Kiro. Wraps kiro-cli in a self-correcting bash loop that picks up tasks from a Kiro spec, implements them one at a time, verifies against exit criteria, and accumulates corrections and codebase patterns across iterations. Use this skill when the user mentions "ralph loop", "ralph", "spec loop", "iterative spec runner", "run my spec tasks automatically", "kiro spec automation", "self-correcting agent loop", "implement spec tasks in a loop", "run kiro-cli in a loop", "automated task implementation", or wants to drive a Kiro spec to completion through repeated agent iterations. Also use when the user wants to set up, configure, troubleshoot, or understand the Ralph Loop workflow — including progress tracking, corrections, codebase patterns, timing logs, and the summary dashboard.
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 tests in red or expand mode and run-and-heal new tests. Use when the user says "lets expand test coverage", "I want to automate tests", "lets write acceptance tests", or "I want to do ATDD"
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。
Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule.
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。
Run an automated smoke test using the godot-mcp server. Launches the project, captures debug output, and checks for errors or crashes.
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 automated API and end-to-end tests for implemented features. Use when the user says "create qa automated tests for [feature]"
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。
Audit and redesign AI-generated feedback for pedagogical quality, timing, and learning impact. Use when building or reviewing automated feedback in digital learning tools.
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。
When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," "lifecycle emails," "trigger-based emails," "email funnel," "email workflow," "what emails should I send," "welcome series," or "email cadence." Use this for any multi-email automated flow. For cold outreach emails, see cold-email. For in-app onboarding, see onboarding.
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。
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment 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。
Generate end to end automated tests for existing features. Use when the user says "create qa automated tests for [feature]"
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 manual tests of the project's running app. Runs a session in one of five modes: exploratory, verification, smoke, assessment (UX, localization, accessibility, improvement review), or AI probe. Also writes a manual test plan that holds only what automated tests cannot judge. Use whenever the user asks, in any language, for something to be tested by hand or for a manual test plan — "manual test", "exploratory test", "bug hunt", "verify the bug fix", "smoke test", "QA this screen", "review this screen's UX", "what would you improve", "check the localized copy", "test the AI agent's answers", "write manual test cases", "kịch bản test manual" — or assigns a test design, test plan or test-case IDs to execute by hand. Not for writing automated tests.
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。
Amazon Bedrock Automated Reasoning for mathematical verification of AI responses against formal policy rules with up to 99% accuracy. Use when validating healthcare protocols, financial compliance, legal regulations, insurance policies, or any domain requiring deterministic verification of AI-generated content.
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 automated regression suites — golden sets, threshold alerting, CI integration for model changes. Use when asked to "catch model regressions in CI", "build a golden set", or "automate eval regression".
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。
Power Platform ソリューションの全体アーキテクチャを設計する。Copilot Studio / Power Automate / Code Apps / Copilot Managed Runtime / Power Pages / AI Builder の使い分け判断、コンポーネント選定、統合パターンを決定する。社内向け画面は利用者のライセンス（Power Apps Premium か、Copilot Credits の従量課金か）と利用頻度をヒアリングし、Code Apps と Copilot Managed Runtime を使い分ける。構成が確定したら、実装着手前に admin スキルで環境チェック（既定環境ではないか・マネージド環境・Code Apps / MCP の有効化・セキュリティ ロール）と DLP 事前チェック（使用コネクタがブロックされていないか・Business / Non-business が混在しないか）を実行して結果をユーザーに提示する。Agent 365 の AI チームメイトを採用する場合はライト実装（PoC）と本格実装（private リポジトリ + CI/CD + Agent Evals）を AskUserQuestion で選ばせ、Git ホスティング（GitHub / Azure DevOps Repos / その他）も確定してから実装へ進む。外部の文章を読むエージェントではプロンプト インジェクション対策を設計段階で工数に含める。
AI Builder の AI プロンプト（GPT Dynamic Prompt）を Dataverse API で作成し、Copilot Studio エージェントにツール（アクション）として追加する。Power Automate フローとの統合パターンも含む。
Use this skill when controlling the AltirraSDL Atari emulator programmatically — driving the simulator from a script, capturing screenshots from a running Atari, injecting joystick/keyboard input, frame-stepping for deterministic testing, reading or writing CPU/memory/chip state, setting breakpoints or watchpoints, profiling 6502 code, loading symbols, or building automated tests against an Atari binary. Triggers on phrases like "AltirraBridge", "AltirraSDL --bridge", "AltirraBridgeServer", "Altirra Python SDK", "headless Atari emulator", "screenshot the Atari", "automate AltirraSDL", "drive the emulator from Python", "Atari debugger over a socket", "altirra_bridge package", as well as on tasks involving the bridge protocol, the Python `altirra_bridge` package, or the C `altirra_bridge.h` SDK.
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 on-target verification of a program's logic by driving its RTT console with rttsh - write Lua scripts that exercise commands and assert responses, output and timing on real hardware. Use when asked to verify target-side behavior on board, build board-level checks for firmware features, or automate hardware test runs.
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。
ActivityWatch is a privacy-first, open-source automated time tracker that records application usage, browser activity, and AFK status across Windows, macOS, and Linux. With 16k+ GitHub stars, it provides detailed productivity analytics without sending data to external servers.
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 GitOps continuous delivery using Argo CD or Flux with app-of-apps pattern, automated sync policies, drift detection, and multi-environment promotion. Manage Kubernetes deployments declaratively from Git with automated reconciliation. Use when implementing declarative infrastructure management, migrating from imperative kubectl commands to Git-driven deployments, setting up multi-environment promotion workflows, enforcing code review gates for production, or meeting audit and compliance requirements.
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。
Executes QA test cases created by $aif-qa in human-guided or automated-agent mode. Use when you need to walk through QA one case at a time, record pass/fail results, or have an agent verify cases through browser, CLI, API, automated tests, or file/document 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。
Executes QA test cases created by /aif-qa in human-guided or automated-agent mode. Use when you need to walk through QA one case at a time, record pass/fail results, or have an agent verify cases through browser, CLI, API, automated tests, or file/document 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。
Executes QA test cases created by $aif-qa in human-guided or automated-agent mode. Use when you need to walk through QA one case at a time, record pass/fail results, or have an agent verify cases through browser, CLI, API, automated tests, or file/document 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。
End-to-end automated model quantization and accuracy tuning workflow. Use when user asks for automated model quantization and accuracy tuning, e.g. "自动量化", "量化调优", "一键量化", "精度调优", etc. 当用户给出多卡（≥2 卡）卡号时，量化阶段通过 EP 并行适配（msmodelslim-ep-parallel-adaptation）保证多卡 EP 并行，调优主流程仍在本 Skill。
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。