「pip」の検索結果

Create, generate, or scaffold GitHub Actions workflows, action.yml, or .github/workflows CI/CD pipelines.

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, generate, or scaffold .gitlab-ci.yml pipelines, stages, and 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。

Generate/create/scaffold Jenkinsfile — declarative, scripted, shared library, CI/CD pipelines.

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。

Production texture workflow for atlases, baking AO/curvature/normal/roughness maps, decals, and texture memory optimization. Use for game-ready texture pipelines in Blender via MCP.

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。

Dedicated LOD generation, naming, screen-size targets, and validation for game meshes in Blender via MCP.

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。

Procedural asset creation for rocks, buildings, vegetation, roads, terrain, pipes, cables, and sci-fi panels using Geometry Nodes and modifier-based workflows in Blender via MCP.

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 starting any Blender asset task, planning a production pipeline, coordinating multiple disciplines, or matching a reference photo/concept art. Invoke for game-ready assets, hard surface, environment, character, creature, export, or any multi-skill Blender workflow.

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。

AAA environment art for modular kits, buildings, terrain, vegetation, architecture, and scene composition. Use for game-optimized environments, storytelling through space, and modular asset pipelines in Blender via MCP.

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。

Production export from Blender to FBX, GLTF, OBJ, USD, and Alembic with scale, pivot, rotation, normals, materials, animation, and collision verification via MCP.

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 complete Spring Boot 4 request path is reactive: WebFlux controllers, Reactor pipelines, R2DBC persistence, streaming, backpressure, or cancellation. For defining and registering declarative outbound API interfaces, use http-interface-clients.

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 complete Spring Boot 3 request path is reactive: WebFlux controllers, Reactor pipelines, R2DBC persistence, streaming, backpressure, or cancellation. For defining and registering declarative outbound API interfaces, use http-interface-clients.

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 integrating LLMs, chat clients, embeddings, RAG pipelines, or AI agents into Spring Boot. Covers Spring AI 2.0 ChatClient, prompt templates, embeddings, vector stores, and structured output. Use when user mentions Spring AI, LLM, ChatGPT, Claude, RAG, embeddings.

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 batch jobs, ETL pipelines, scheduled imports/exports, or any chunk-oriented bulk processing with Spring Batch. Covers the Spring Batch 5 / Boot 3 builder API, restartability and idempotent job parameters, reader/writer thread-safety, fault tolerance, and chunk transaction boundaries.

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 batch jobs, ETL pipelines, scheduled imports/exports, or any chunk-oriented bulk processing with Spring Batch. Covers the Spring Batch 6 / Boot 4 builder API, resourceless vs JDBC job repositories, restartability and idempotent job parameters, reader/writer thread-safety, fault tolerance, and chunk transaction boundaries.

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 integrating LLMs, chat clients, embeddings, RAG pipelines, or AI agents into Spring Boot. Covers Spring AI ChatClient, prompt templates, embeddings, vector stores, and structured output. Use when user mentions Spring AI, LLM, ChatGPT, Claude, RAG, embeddings.

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。

Designs event-driven architectures, webhook systems, API chaining flows, ETL pipelines, and integration patterns between 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。

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

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。

Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.

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。

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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 to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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 planning a modeling solution, selecting the next useful step or briefing a specialist.

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 cookie consent validation using Selenium and Playwright. Covers banner interaction testing, consent state verification, tag firing audit after consent choices, regression testing for cookie compliance, and CI/CD pipeline 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。