「testing」の検索結果

The fastest way to get started with TestDriver. Just set your API key and start 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。

Updates an existing package Skill for a new release of its npm or local package by testing only what changed since the version the Skill names. Use when a maintainer asks to refresh a package Skill after a release, or when a SKILL.md names an older tested version than the package.

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 skill should be used when the user asks about "theme", "controlling idea", "thematic argument", "moral argument", "thematic arc", "flat arc", "negative arc", "the lie", "antagonist design", "motif", "symbolism", "theme audit", or wants to plan, track, or revise the thematic layer of a story, including the lie, truth, ghost-wound, and arc-type fields of a character file. NOT for finding or testing a story premise (use premise-workshop), or a character's profile, relationships, or "character arc" record (use character-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。

POS unit testing patterns (WooPosCoroutineTestRule, runTest, advanceUntilIdle, mockito-kotlin, event bus mocking, analytics verification). Use when writing, editing, exploring, debugging, or reviewing unit tests for POS (WooPos*) code. NOT for main store app tests — use the `store-tests` 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。

Main app unit testing patterns (BaseUnitTest, BDD naming, mockito-kotlin, AssertJ, StateFlow/LiveData capture, coroutine dispatchers). Use when writing, editing, exploring, debugging, or reviewing unit tests in the store management app. For POS (WooPos*) tests, use the `pos-tests` 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。

Financial trading CLIs — spot and perp trading on Hyperliquid, Binance, Coinbase, OKX. Prediction markets on Polymarket. Deposit and withdraw across chains. LLM-enriched price quotes with trend analysis. News and SEC filings. Historical backtesting with forward PnL analysis. Use when: user asks about stock/crypto prices, wants to trade, deposit, withdraw, check portfolio, or backtest a strategy.

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。

Guides SOC 2 Type II Privacy Trust Services Criteria preparation and audit execution. Covers AICPA TSP Section 100 Privacy criteria P1-P8 including notice, choice/consent, collection, use/retention/disposal, access, disclosure, security, and quality. Includes evidence collection, control testing, and report review. Keywords: SOC 2, privacy criteria, TSP, AICPA, Type II, trust 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。

Universal opt-out mechanism implementation across US state privacy laws. Covers Global Privacy Control (GPC) signal technical implementation, state-by-state recognition requirements, browser detection methods, authenticated vs unauthenticated handling, and compliance 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。

Implements email and internet monitoring compliance in the workplace per Barbulescu v Romania (ECHR Grand Chamber), EDPB guidance, and national labour law. Covers acceptable use policies, legitimate expectation of privacy, proportionality testing, and content vs metadata monitoring. Keywords: email monitoring, Barbulescu, workplace privacy, internet monitoring, acceptable use policy, ECHR, proportionality.

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。

Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management. Applies Art. 9(2)(b) employment obligations and Art. 9(2)(h) health professional exceptions. Covers data minimisation, occupational health provider relationships, and return-to-work procedures. Keywords: health data, Art. 9, occupational health, fitness-for-work, special category, employment, sickness absence.

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。

Conducts Data Protection Impact Assessments for employee monitoring systems per EDPB Guidelines 3/2019 on workplace data processing. Covers video surveillance, email monitoring, GPS tracking, keystroke logging, and productivity tools. Applies proportionality testing under Art. 35 GDPR. Keywords: DPIA, employee monitoring, surveillance, proportionality, EDPB, workplace privacy, keystroke logging, GPS 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。

Framework for evaluating and selecting Consent Management Platforms (CMPs). Covers TCF v2.2 certification requirements, Global Privacy Control support, multi-regulation compliance (GDPR, CCPA, LGPD), A/B testing capabilities, API integration options, reporting features, and a structured vendor comparison methodology.

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。

Guides continuous privacy compliance monitoring implementation including automated control testing, evidence collection automation, real-time compliance dashboards, alert-based remediation workflows, regulatory change integration, and deviation management. Covers GRC platform configuration, control framework mapping, and compliance-as-code approaches. Keywords: continuous compliance, automated monitoring, evidence collection, dashboard, regulatory change, compliance-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。

Implements strict data minimization and retention limits for children's personal data under GDPR Art. 5(1)(c), Recital 38, UK AADC Standard 8, and COPPA Section 312.7. Covers strict necessity testing, shorter retention periods, limited profiling, parental dashboard design, and automated deletion. Keywords: data minimization, children, retention, necessity test, parental 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。

Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment monitoring setup. Keywords: AI deployment, privacy checklist, go-live, model deployment, compliance gate.

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。

Generates production-grade Appium mobile automation scripts for Android and iOS in Java, Python, or JavaScript. Supports real device and emulator testing locally and on TestMu AI cloud with 100+ real devices.

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。

Authorized security assessment of REST, GraphQL, WebSocket, and SOAP APIs: discovery, authentication and authorization flaws (BOLA/IDOR, JWT/OAuth), rate-limit testing, and a structured multi-phase methodology.

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 end-to-end UI testing and verification on an Android Emulator using ADB.

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 production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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。

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance 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。

When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program.

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。

Provide comprehensive techniques for attacking Microsoft Active Directory environments. Covers reconnaissance, credential harvesting, Kerberos attacks, lateral movement, privilege escalation, and domain dominance for red team operations and penetration 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。

Debug, patch, and verify failed Agent QA runs from MCP evidence, artifacts, logs, and local code without hiding product or infrastructure defects.

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 failed Agent QA runs with MCP evidence, artifacts, logs, fixed failure categories, confidence, and actionable next 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。