「integration」の検索結果

Plan, write, and maintain automated tests in any language, with worked examples in Python and JavaScript/TypeScript. Use this skill whenever the user wants to write or plan tests, apply TDD (red-green-refactor), structure unit tests with arrange-act-assert and given-when-then naming, choose between fakes, stubs, and mocks, set up dependency injection for testability, build integration tests with testcontainers, database seeding, or transaction rollback, write Playwright or Cypress end-to-end tests, use property-based testing with Hypothesis or fast-check, create pytest fixtures or factory_boy factories, review coverage or mutation testing, or triage flaky tests in CI. Also trigger for "test pyramid", "test trophy", "test isolation", "mocking", "snapshot tests", "golden files", "parametrized tests", "make the tests pass".

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 AI agents with LangChain framework. Use when building agents, tools, memory, MCP integrations, RAG pipelines, multi-agent systems, or any LLM-powered applications using LangChain or LangGraph in Python or TypeScript.

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 AI agents with Hugging Face's SmolAgents framework. Use when creating code-executing agents, tool-calling agents, multi-agent systems, agentic RAG, text-to-SQL pipelines, web browsing agents, or any multi-step AI workflows. Covers CodeAgent, ToolCallingAgent, custom tools, MCP integration, memory management, secure code execution (E2B, Docker, Blaxel), and model configuration (HF Inference, LiteLLM, Transformers, Ollama).

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 SwiftUI guidance for macOS apps — covers writing and reviewing code with runtime-level understanding of observation, concurrency, performance, and platform integration. Use when user asks to "build a SwiftUI view", "review my SwiftUI code", "fix observation issues", "bridge AppKit", "architect state management", "debug view updates", or works on any macOS SwiftUI project — building features, reviewing existing code, debugging view updates or performance, fixing concurrency issues, architecting state management, bridging AppKit, or making design decisions. Do NOT use for iOS/iPadOS-only SwiftUI, UIKit bridging, or basic Swift language questions. Focuses on non-obvious traps and deep patterns, not basics.

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 the user asks for a multi-agent .NET code review - five parallel reviewers (correctness, performance, security/observability, data/messaging/integration, generalist) plus an adversarial maintainer that refutes weak findings. Requires the review agent roles registered by scripts/install-codex.sh. Keywords: dotnet review pipeline, multi-agent review, parallel reviewers, maintainer pushback, review this branch, cynical review.

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 the user shares a Sentry URL, says "check Sentry", or wants to investigate production errors. Uses Sentry MCP tools for deep analysis.

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 the user says "check Jira", "create ticket", "update issue", or needs JQL queries, ticket transitions, or branch-to-ticket linking.

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 building or maintaining a Composer library — versioning, Laravel integration, autoloading, publishing to private registries — even when the user says 'release a new version'.

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 writing API endpoint tests — integration tests, contract validation, response assertions, mocked external services — even when the user says 'test this route' without naming API 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。

Use when deciding insource vs outsource vs acquire — integration-cost analysis, dependency-risk, optionality preservation. Triggers on 'should we build', 'buy vs partner'.

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, running, or debugging proctmux end-to-end integration tests, especially PTY/TUI behavior, terminal snapshots, unified/client modes, timing flakes, VT100 emulator limits, or files under tests/e2e and internal/testharness/e2e.

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。

Quantização de pesos consciente da ativação para compressão de LLM de 4-bit com aceleração 3x e perda mínima de acurácia. Use ao implantar modelos grandes (7B-70B) em memória GPU limitada, quando precisa de inferência mais rápida que GPTQ com melhor preservação de acurácia, ou para modelos com instruções ajustadas e multimodais. Vencedor do Prêmio Melhor Artigo MLSys 2024.

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 this skill when configuring axe-core scans, reviewing automated accessibility test results, or writing tests that use @axe-core/playwright, @axe-core/react, or similar integrations. Provides a quick reference to axe 4.x rule IDs, their WCAG mapping, and default severity levels.

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。

[Workflow] Use when activating the Greenfield Project Init workflow for full waterfall project inception from idea through implementation with integration 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。

[Documentation] Use when scanning the codebase to (re)generate ONE project-reference doc. Parameterized by `--target=<key>`: project-structure | backend-patterns | frontend-patterns | scss-styling | design-system | code-review-rules | domain-entities | feature-spec | docs-index | e2e-tests | integration-tests | seed-test-data | ui-system. Shared 4-phase scan engine; per-target detail lives in references/targets.md. `ui-system` is an orchestrator meta-target (`kind: orchestrator`) that runs the 3 UI child scans in parallel instead of the 4-phase engine.

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。

[Architecture] Use when you need to analyze business domain: bounded contexts, aggregates, entities, ERD, domain events, and cross-context 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。

[Architecture] Use when designing solution architecture across backend, frontend, data & consistency, integration & APIs, deployment, monitoring, testing, and code quality. Architecture laws, style-selection triggers, coupling taxonomy, trade-off tables and the anti-pattern catalog live in `.claude/docs/architecture-knowledge.md`.

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。

Evaluates potential channel, integration, affiliate, or strategic partners. Use when the user provides partner profiles plus partnership goals and wants fit scoring, partnership type, and outreach priority.

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。

Remove Gemini AI watermarks from images using GeminiWatermarkTool (GWT). Use this skill whenever the user mentions: Gemini watermark, 浮水印, AI image cleanup, removing logos from Gemini-generated images, Google ImageFX cleanup, batch processing AI-generated photos, or anything about a semi-transparent logo in the bottom-right corner of an image — even if they don't say "GeminiWatermarkTool" explicitly. Also trigger for follow-up requests like "the corner still looks dirty" or "there's still residual artifacts" after a previous removal attempt.

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。

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration 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。

Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.

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。

Search PubMed biomedical literature with natural language queries powered by Valyu semantic search. Full-text access, integrate into your AI projects.

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。

Patient safety evaluation harness for healthcare application deployments. Automated test suites for CDSS accuracy, PHI exposure, clinical workflow integrity, and integration compliance. Blocks deployments on safety failures. Use when a healthcare deployment must be gated on patient-safety tests for CDSS accuracy, PHI exposure, and workflow integrity.

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。

EMR/EHR development patterns for healthcare applications. Clinical safety, encounter workflows, prescription generation, clinical decision support integration, and accessibility-first UI for medical data entry. Use when building EMR or EHR features such as encounter workflows, prescription generation, or clinical data entry UI.

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。