「validate」の検索結果

Generates complete CRUD modules for NestJS applications with Drizzle ORM. Use when building server-side features in NestJS that require database operations, including creating new entities with full CRUD endpoints, services with Drizzle queries, Zod-validated DTOs, and unit tests. Triggered by requests like "generate a user module", "create a product CRUD", "add a new entity with endpoints", or when setting up database-backed features in NestJS.

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。

Creates reusable Zod v4 schemas, validates API payloads, forms, and configuration input, transforms and coerces data safely, and handles validation errors with strong type inference for TypeScript applications. Use when designing validation layers, parsing `z.string()`, `z.object()`, or `z.email()` schemas, or implementing runtime type-safe data validation.

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。

Provides patterns for unit testing Spring Security with `@PreAuthorize`, `@Secured`, `@RolesAllowed`. Validates role-based access control and authorization policies. Use when testing security configurations and access control logic.

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。

Provides patterns for unit testing external REST APIs using WireMock. Stubs API responses, verifies request details, simulates failures (timeouts, 4xx/5xx errors), and validates HTTP client behavior without real network calls. Use when testing service integrations with external APIs or mocking HTTP endpoints.

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。

Provides comprehensive memory file management capabilities including auditing, quality assessment, and targeted improvements for files such as CLAUDE.md. Use when user asks to check, audit, update, improve, fix, maintain, or validate project memory files. Also triggers for "project memory optimization", "CLAUDE.md quality check", "documentation review", or when a project memory file needs to be created from scratch. This skill scans memory files, evaluates quality against standardized criteria, outputs detailed quality reports with scores and recommendations, then makes targeted updates with user approval.

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。

Provides patterns for unit testing Spring application events. Validates event publishing with ApplicationEventPublisher, tests @EventListener annotation behavior, and verifies async event handling. Use when writing tests for event listeners, mocking application events, or verifying events were published in your Spring Boot 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。

Provides patterns for unit testing Jakarta Bean Validation (JSR-380), including @Valid, @NotNull, @Min, @Max, @Email constraints with Hibernate Validator. Generates custom validator tests, constraint violation assertions, validation groups, and parameterized validation tests. Validates data integrity logic without Spring context. Use when writing validation tests, bean validation tests, or testing custom constraint validators.

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。

Provides patterns for implementing Spring Boot caching: configures Redis/Caffeine/EhCache providers with TTL and eviction policies, applies @Cacheable/@CacheEvict/@CachePut annotations, validates cache hit/miss behavior, and exposes metrics via Actuator. Use when adding caching to Spring Boot services, configuring cache expiration, evicting stale data, or diagnosing cache misses.

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。

Provides fault tolerance patterns for Spring Boot 3.x using Resilience4j. Use when implementing circuit breakers, handling service failures, adding retry logic with exponential backoff, configuring rate limiters, or protecting services from cascading failures. Generates circuit breaker, retry, rate limiter, bulkhead, time limiter, and fallback implementations. Validates resilience configurations through Actuator endpoints.

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。

Provides unit test, integration test, and mock AI patterns for LangChain4j applications. Creates mock LLM responses, tests retrieval chains, validates RAG workflows, and implements Testcontainers-based integration tests for Java AI services. Use when unit testing AI services, integration testing LangChain4j components, mocking AI models, or testing LLM-based Java applications.

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。

Provides edge case, corner case, boundary condition, and limit testing patterns for Java unit tests. Validates minimum/maximum values, null cases, empty collections, numeric overflow/underflow, floating-point precision, and off-by-one scenarios using JUnit 5 and AssertJ. Use when writing .java test files to ensure code handles limits, corner cases, and special inputs correctly.

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。

Provides and generates LangChain4j tool and function calling patterns: annotates methods as tools with @Tool, configures tool executors, registers tools with AiServices, validates tool parameters, and handles tool execution errors. Use when building AI agents that call tools, define function specifications, manage tool responses, or integrate external APIs with LLM-driven applications.

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。

Provides chunking strategies for RAG systems. Generates chunk size recommendations (256-1024 tokens), overlap percentages (10-20%), and semantic boundary detection methods. Validates semantic coherence and evaluates retrieval precision/recall metrics. Use when building retrieval-augmented generation systems, vector databases, or processing large documents.

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。

Provides and generates complete CRUD workflows for Spring Boot 3 services. Creates feature-focused architecture with Spring Data JPA aggregates, repositories, DTOs, controllers, and REST APIs. Validates domain invariants and transaction boundaries. Use when modeling Java backend services, REST API endpoints, database operations, web service patterns, or JPA entities for Spring Boot applications.

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 needs to estimate market size, understand market dynamics, or validate that a market opportunity is large enough to pursue.

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 game-ready fixed-cell pixel-art character spritesheets from text concepts, reference images, or existing character art. Use when Codex needs to design, generate, clean up, validate, and package 2D game characters with native 32x32, 64x64, or 128x128 cells; 4-way or 8-way directions; idle, walk/run, jump, attack, archer, caster, or other animation strips; transparent GIF/WebP previews; and per-direction targeted regeneration.

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 construction payment applications. Validate schedule of values, calculate retainage, track billing status, and generate G702/G703 forms.

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 construction data inputs before processing: cost estimates, schedules, BIM data, field reports. Catch errors early with domain-specific rules.

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。

Check BIM data against IDS (Information Delivery Specification). Validate model information requirements and compliance.

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。

Check data compliance with construction standards. Validate data against ISO 19650, IFC, COBie, UniFormat standards.

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 pipeline for retraining ML models with new construction data. Monitor model drift, trigger retraining, and validate model performance.

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。

Parse and validate JSON data from construction APIs, IoT sensors, and BIM exports. Transform nested JSON to flat DataFrames.

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。

Match BIM quantities to CWICR work items. Map element categories to cost codes, validate quantities, and generate cost-linked QTOs.

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 CWICR data quality and estimate inputs. Check for errors, inconsistencies, outliers, and missing data.

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。