「automated」の検索結果

Test application security against OWASP Top 10 (2025) with automated CI tooling: OWASP ZAP (DAST), dependency/supply-chain scanning (OSV-Scanner, SBOM, provenance), Semgrep SAST, auth/session tests (JWT, OAuth, RBAC), and XSS/CSRF/SQLi/SSRF Playwright patterns. Use when: "security test," "OWASP," "vulnerability," "ZAP," "XSS," "SSRF," "dependency scan," "auth testing," "OWASP LLM Top 10." Scope is automated scanning + negative-path security tests in CI, not manual penetration testing. Not for: mapping security controls to regulations (SOC 2, HIPAA, PCI, GDPR) — use compliance-testing; pipeline stage wiring and deploy gating mechanics — use ci-cd-integration; purely functional API auth/input tests with no attacker model — see api-testing; testing your product's own LLM features or defending the agent itself (prompt-injection detector, indirect injection, jailbreak red-teaming) — use ai-system-testing. Related: ci-cd-integration, compliance-testing, api-testing, shift-left-testing, ai-system-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。

Expert in integrating Claude Code with CI/CD pipelines. Covers headless mode for non-interactive execution, GitHub Actions and GitLab CI/CD integration, automated code review, issue triage, and PR workflows. Essential for teams wanting AI-powered automation in their development pipelines. Use when "claude code CI/CD, headless mode, GitHub Actions claude, GitLab CI claude, automated code review, PR automation, issue triage, claude-code, cicd, automation, github-actions, gitlab, headless, pipeline, devops" mentioned.

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 patterns for building AI-powered code generation tools, code assistants, automated refactoring, code review, and structured output generation using LLMs with function calling and tool use. Use when "code generation, AI code assistant, function calling, structured output, code review AI, automated refactoring, tool use, code completion, agent code, " mentioned.

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。

Template-based page generation at scale for SEO. Data-driven content, internal linking architecture, and automated optimization for large-scale content operations. Use when the user asks about programmatic SEO, pSEO, scaled content, template pages, or automated page generation.

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。

AWS Cost Cleanup workflow skill. Use this skill when the user needs Automated cleanup of unused AWS resources to reduce costs 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。

AWS Cost Cleanup workflow skill. Use this skill when the user needs Automated cleanup of unused AWS resources to reduce costs 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。

Android UI Verification Skill workflow skill. Use this skill when the user needs Automated end-to-end UI testing and verification on an Android Emulator using ADB 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。

Android UI Verification Skill workflow skill. Use this skill when the user needs Automated end-to-end UI testing and verification on an Android Emulator using ADB 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。

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。

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。

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。