「dpo」の検索結果

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.

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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。

Connect OpenConstructionERP to AI coding assistants via MCP (Model Context Protocol): expose costs, BOQ, BIM and catalog endpoints as MCP tools so Claude Code / Antigravity / OpenCode can drive the platform. Use when wiring an assistant to the ERP.

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。

Guide to OpenConstructionERP: architecture, modules, API surface and quick start. Use when starting any OpenConstructionERP work, onboarding a user to the platform, or deciding which module/endpoint to use.

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Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_prep_search, ai_query, ai_forecast) to add AI capabilities directly to SQL and PySpark pipelines without managing model endpoints. Also covers document parsing and building custom RAG pipelines (parse → prep_search → index → query).

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。

Train ML models on Databricks. Use for: classification/regression/deep-learning (XGBoost, scikit-learn, LightGBM, PyTorch) with Optuna, @prod/@challenger aliases, batch scoring (spark_udf for plain models, fe.score_batch for feature-store-backed), custom PyFunc, custom ResponsesAgent (LangGraph + UC Function/Vector Search); UC feature tables + FeatureLookup + point-in-time joins + Lakebase online store; declarative Feature Views (create_feature, DeltaTableSource, RollingWindow/SlidingWindow/TumblingWindow, materialize_features, streaming Kafka features). NOT for: endpoint ops (databricks-model-serving), MLflow evaluation (databricks-mlflow-evaluation).

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。

Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns

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 comprehensive API documentation including endpoint descriptions, request/response examples, authentication guides, error codes, and SDKs. Creates OpenAPI/Swagger specs, REST API docs, and developer-friendly reference materials. Use when users need to document APIs, create technical references, or write developer documentation.

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。

Load tests API endpoints with progressive concurrency. Measures response times, error rates, throughput, and identifies breaking points. Generates a detailed report with latency percentiles, throughput curves, bottleneck analysis, and optimization recommendations.

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Compress-Cache-Retrieve for huge, repetitive array tool output (logs, scan results, time series, event streams) before it enters context. Keeps an informative sample — endpoints, anomalies/change-points, head/tail — drops the redundant rest to a local cache, and leaves a retrievable hash. Use when a tool returns a long uniform JSON array you must read but mostly skim, and the full set is one command away if needed. Lossy-but-recoverable.

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Design privacy API patterns including data subject API for DSAR endpoints, consent API for preference management, deletion API with cascading delete orchestration, and audit API for compliance reporting. Provides OpenAPI specifications, error handling, rate limiting, and authentication patterns.

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Builds a comprehensive breach response team playbook defining CSIRT and privacy team structure with named roles (incident commander, legal counsel, communications, IT forensics, DPO), escalation matrices, communication templates, pre-negotiated vendor contacts, and regulatory authority contacts organized by jurisdiction. Keywords: breach response playbook, CSIRT, incident response team, escalation matrix, communication templates, vendor contacts.

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Guides compliance with Brazil's Lei Geral de Proteção de Dados (LGPD, Lei 13.709/2018). Covers the 10 lawful bases under Art. 7, DPO appointment, ANPD enforcement, data subject rights under Arts. 17-22, and international transfer mechanisms. Keywords: LGPD, Brazil data protection, ANPD, lawful bases, data subject rights, international transfers.

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 when organizing or verifying a modular Spring Boot monolith with Spring Modulith, including module APIs, dependency rules and reliable module events. Do not restructure an application into modules for an unrelated endpoint change.

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 penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations.

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 comprehensive, developer-friendly API documentation from code, including endpoints, parameters, examples, and best practices

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 complete, production-ready REST API endpoint specifications for any system or domain the user describes.

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 stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.

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Compiled CLI covering all 52 endpoints of the Anytype local API — objects, properties, tags, search, chat, files — one binary, no MCP server needed.

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Adds, changes, or reviews a screen, sheet, dialog, or destination slice (endpoint to repository to ViewModel to UI to navigation to DI to tests) in a Compose or CMP project. Use when adding a screen, building a new feature, adding a ViewModel or destination, wiring list/detail or a form screen, scaffolding a slice, or reviewing a feature change. Covers Contract.kt, launchGuarded wiring, SavedStateHandle drafts, the state matrix, and new-feature.sh. Do NOT use for routing or architecture (compose-architecture), pure refactors, Gradle work (compose-project), recomposition or styling (compose-ui), repository or persistence work (compose-data), or expect/actual splits (compose-platform).

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 when adding or changing what the rezolus viewer exposes — an /api/v1 endpoint, a dashboard section, the metric catalog, metadata/description derivation, or the frontend data those depend on — or when editing src/viewer/ or crates/viewer/, or reviewing a viewer change. The viewer ships as two separate Rust backends (server + WASM) behind one shared frontend; changing one silently diverges them.

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 the end-to-end viewer smoke test (`tests/viewer_smoke.sh`). Spawns `rezolus view` in upload-only, file, A/B, and proxy modes, exercises the API endpoints, and verifies experiment attach/detach. Use after any change touching `src/viewer/` or before opening a viewer-related PR.

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。

Work with the QStash JavaScript/TypeScript SDK for serverless messaging, scheduling. Use when publishing messages to HTTP endpoints, creating schedules, managing queues, verifying incoming messages in serverless environments.

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。

Fix JSON parse errors when fetching archived API responses from Wayback Machine. Use when: (1) Getting "Expecting value: line 1 column 1 (char 0)" JSON decode errors from archived URLs, (2) Wayback returns HTML instead of expected JSON/raw content, (3) Crawling archived REST APIs or JSON endpoints from web.archive.org. The `id_` modifier returns raw content without the Wayback toolbar wrapper.

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。