「automation」の検索結果

Sequenced launcher that bootstraps QA on a project with no QA in place. Chains qa-project-context → test-strategy → test-planning in one guided run, then points you at automation. Use when: "set up QA on a new project," "QA from scratch," "no QA exists yet," "/qa-start." Not for: onboarding a QA engineer to an existing team with existing tests — use qa-project-bootstrap. Not for: "which skill do I use" with no clear match — use qa-do. Related: qa-project-context, test-strategy, test-planning, qa-project-bootstrap, qa-do.

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 effective unit tests with Jest, Vitest, or pytest. Covers the test-doubles taxonomy (stub/spy/mock/fake), Arrange-Act-Assert, coverage threshold configuration and CI gating, snapshot testing, fake timers, and mutation testing with Stryker/mutmut. Use when: "unit test," "Jest," "Vitest," "pytest," "mock," "coverage threshold," "test doubles," "mutation testing," "fake timers," "snapshot test." Not for: interpreting coverage reports or finding coverage gaps — use coverage-analysis; AI generating the test code for you — use ai-test-generation; auditing existing tests for smells — use ai-qa-review; browser/component rendering assertions — use cypress-automation or visual-testing. Related: coverage-analysis, ci-cd-integration, ai-test-generation, shift-left-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。

Validate that analytics and marketing tracking fire CORRECTLY: GA4/GTM dataLayer events, Meta/TikTok/LinkedIn pixels, and ad-tech tags. Covers building a tracking plan as the contract, intercepting collect-endpoint beacons and dataLayer.push in Playwright, asserting event name + params + values + timing + de-duplication, Consent Mode v2 gating, CI regression gating, and news-media events (article-view, scroll-depth, paywall). Use when: "test analytics tracking," "GA4 event test," "verify the pixel fires," "dataLayer test," "tracking plan," "Meta Pixel dedup," "scroll-depth tracking test," "gate tracking in CI." Not for: whether tracking is ALLOWED to fire under consent law (GDPR/CMP) — that is compliance-testing; this skill checks the data is CORRECT. SEO meta tags / structured data — out of scope. Related: compliance-testing, playwright-automation, api-testing, qa-project-context.

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 testing of email-dependent flows — signup confirmation, password reset, magic-link login, OTP/MFA codes, and notification emails. Covers the capture-inbox decision tree (Mailpit, Mailosaur, MailSlurp, Ethereal), Playwright polling without fixed sleeps, regex extraction of links/OTPs from the email body, deterministic per-test addresses (plus-addressing, per-inbox), subject/from/header/link assertions, and SPF/DKIM/DMARC deliverability checks as a separate suite. Use when: "test the signup confirmation email," "password reset email test," "magic-link login test," "capture OTP from email," "Mailpit," "Mailosaur," "MailSlurp," "email arrives flaky in CI," "assert email subject/from/links." Not for: Sending transactional email from your app code, or API-only contract tests of an email provider — those are api-testing / app concerns. Email HTML rendering across clients (Outlook/Gmail dark mode) is out of scope (note it as a gap; use visual-testing or Litmus). Related: playwright-automation, api-testing, test-data-management, qa-project-context.

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 analytics-driven browser test matrices and execute cross-browser tests. Covers BrowserStack/Sauce Labs configuration, Playwright browser channels, common cross-browser CSS/JS divergences, a known-issues documentation log, and progressive enhancement validation. Use when: "cross-browser," "browser matrix," "BrowserStack," "Safari issues," "browser compatibility," "Edge," "works in Chrome but not Safari." Not for: pixel-level baseline strategy and threshold tuning — use visual-testing; device-farm testing of native/hybrid apps — use mobile-testing. Related: visual-testing, playwright-automation, ci-cd-integration, mobile-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。

Author and maintain MANUAL and hybrid test cases and suites in TestRail, Xray (Jira), Zephyr Scale, and Qase. Covers test-case anatomy (title, preconditions, steps, expected results, test data), suite/section organization, bulk authoring from user stories and acceptance criteria, ambiguous-step linting, CSV/API import-export payloads per tool, requirement traceability and coverage gaps, review hygiene, and when a manual case should graduate to automation. Use when: "write a test case," "manual test case," "TestRail case," "Xray test," "Zephyr Scale case," "Qase case," "import CSV into TestRail," "lint these steps," "traceability report," "should this be automated." Not for: Generating automated TEST CODE — that is ai-test-generation. Sprint-level WHAT-to-test selection — that is test-planning. Related: ai-test-generation, test-planning, exploratory-testing, qa-project-context.

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 AI to write NEW test code from specs, PRDs, user stories, code diffs, bug reports, or OpenAPI specs. Staged pipeline: requirements extraction → risk analysis → coverage matrix → scenario generation → oracle design → test code → human review, with guardrails against hallucinated APIs and weak assertions. Use when: "generate tests from spec," "tests from PRD," "tests from user story," "auto-generate test cases," "AI write tests for me." Not for: testing AI/LLM features in your product — use ai-system-testing. Not for: auditing a pre-existing test suite you did not just generate — use ai-qa-review (Step 7 here only reviews tests THIS pipeline produced). Related: playwright-automation, unit-testing, api-testing, qa-project-context.

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。

Recon-first browser automation. Orchestrator explores the site first via chromux, saves a guide file with insights, then delegates execution to browser-explorer agent. Use when: "/browser-work", "브라우저 작업", "사이트에서 해줘", "웹에서 해줘", "LinkedIn에서", "크롬으로", "browser task", "automate this site".

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 backends and APIs with Directus headless CMS. Use when a user asks to create a headless CMS, build a content API without coding, set up a backend admin panel, create REST or GraphQL APIs from a database, manage content with roles and permissions, build a data platform with auto-generated APIs, or replace traditional CMS with a headless solution. Covers data modeling, auto-generated REST/GraphQL APIs, roles/permissions, flows (automation), file storage, and SDK integration.

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 and script DaVinci Resolve workflows. Use when a user asks to script DaVinci Resolve via Python/Lua API, automate color grading, batch render projects, manage timelines programmatically, automate media import, build render queues, create Fusion compositions via script, automate Fairlight audio processing, manage project databases, build custom tool scripts, or integrate Resolve into production pipelines. Covers the Resolve Scripting API (Python/Lua), Fusion scripting, and workflow 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。

Assists with end-to-end testing of web applications using Cypress. Use when writing E2E tests, setting up component testing, configuring CI pipelines with parallelization, or building custom test commands. Trigger words: cypress, e2e testing, end-to-end, cypress run, cy.get, integration testing, browser 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。

Schedule recurring tasks with cron on Linux/macOS. Use when a user asks to run scripts on a schedule, set up automated backups, schedule data processing, or configure periodic tasks on a server.

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 Codex CLI, Claude Code, or other coding agents as background processes for programmatic control. Use when a user asks to run a coding agent, delegate a task to another AI, spawn a sub-agent, run Claude Code in the background, or orchestrate multiple coding agents on separate tasks.

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 and optimize CI/CD pipelines for GitLab CI and CircleCI. Use when a user asks to set up GitLab CI, create a CircleCI pipeline, build a CI pipeline for GitLab, automate deployments with CircleCI, add test automation to GitLab, or configure continuous integration on non-GitHub platforms. For GitHub Actions pipelines, use the github-actions skill instead.

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。

Manage knowledge bases and documentation with Confluence Cloud. Use when a user asks to create or manage Confluence spaces, pages, and blogs, build documentation systems, automate page creation from templates, use Confluence REST API v2, manage page trees and hierarchies, set up permissions, integrate Confluence with Jira or other tools, generate reports from Confluence data, build macros or Forge apps, or migrate content between spaces. Covers content management, API automation, templates, and Atlassian ecosystem integration.

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。

CodeRabbit reviews pull requests with AI on GitHub, GitLab, Azure DevOps and Bitbucket, and reviews local changes from a CLI before they are pushed. Use when a user asks to set up automated PR reviews, write or validate a .coderabbit.yaml, add path-specific review instructions, control a review with @coderabbitai commands, or run coderabbit review from the terminal or a coding agent.

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 bookkeeping workflows by parsing bank statements (CSV/OFX/QIF), categorizing transactions using rules or AI, reconciling accounts, generating expense reports, and detecting duplicates. Use when: automating transaction categorization, building reconciliation pipelines, processing bank exports, or generating expense summaries without manual data entry.

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 Blender rendering from the command line. Use when the user wants to set up renders, batch render scenes, configure Cycles or EEVEE, set up cameras and lights, render animations, create materials and shaders, or build a render pipeline with Blender Python scripting.

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 Canva from an agent — via the AI Connector MCP server (generate, find, edit, export designs in natural language) or the Connect REST API (OAuth 2.0 + PKCE, brand template autofill, asset uploads, exports, folders, comments). Use when: connecting an agent to Canva, batch-producing social posts or decks from a brand template and a spreadsheet, exporting designs to PDF/PNG/PPTX/MP4, uploading assets into a Canva account, building a Canva integration, or when the user mentions "Canva", "brand template", "autofill", "Connect API", or "mcp.canva.com".

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。

Browser Use is an open-source Python library that lets an LLM agent drive a real browser to navigate sites, fill forms, click and extract data from a plain-English task. Use when the user wants an AI agent to automate a website, scrape pages that need clicking or login, return structured data from the web, add browser tools to a coding agent, or run browser agents locally or in the cloud.

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。

The AWS Command Line Interface (v2) manages Amazon Web Services from the terminal. Use when the user needs to run S3, EC2, Lambda, CloudWatch, IAM or other AWS commands, sign in with SSO or short-term credentials, write AWS automation scripts, or debug an `aws` command and its output.

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。

Process multiple documents in bulk with parallel execution. Use when a user asks to batch process files, convert many documents at once, run parallel file operations, bulk rename, bulk transform, or process a directory of files concurrently. Covers parallel execution, error handling, and progress tracking.

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。

Airtable is a hosted spreadsheet-database; its Web API reads and writes records, table schema, attachments and webhooks over REST. Use when tasks involve reading or writing Airtable data, importing or upserting rows from a CSV or another system, syncing external sources with Airtable bases, reacting to record changes with webhooks, connecting users through Airtable OAuth, or debugging 422 and 429 responses from api.airtable.com.

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。

Covers scripting Autodesk 3ds Max, the 3D modeling and rendering application, with MAXScript and Python (pymxs): scene manipulation, object creation, material assignment, camera and light setup, batch operations, and file I/O. Use when tasks involve automating repetitive 3ds Max workflows, batch processing scenes, running scripts headless with 3dsmaxbatch, creating custom tools, or scripting scene setup for archviz, product visualization, or VFX.

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。