「action」の検索結果

Analyzes PHP codebase for test coverage gaps. Detects untested classes, methods, branches, exception paths, and edge cases. Provides actionable recommendations.

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 Mediator pattern for PHP 8.5. Creates coordination layer for complex component interactions with event dispatching, request/response handling, and colleague classes. Reduces coupling between interacting objects. Includes unit 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。

Transform academic course assignment PDFs into structured, actionable markdown checklists with dates, unique IDs, and custom tags. Asks when the user will start, assigns tasks only to weekdays (Monday-Friday), respects weekends automatically, and calculates forum deadlines 3 days before due date. Use this skill when the user uploads academic PDFs or asks to create a task plan from course assignments.

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。

Analyzes PHP codebase for SOLID principle violations. Detects God classes (SRP), type switches (OCP), broken contracts (LSP), fat interfaces (ISP), and concrete dependencies (DIP). Generates actionable reports with severity levels and remediation recommendations.

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 PHPUnit integration tests for PHP 8.5. Creates tests with real dependencies, database transactions, HTTP mocking. Supports repositories, API clients, message handlers.

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 Transactional Outbox pattern components for PHP 8.5. Creates OutboxMessage entity, repository, publisher, and processor with unit 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。

When the user needs to integrate multiple data sources (Canvas API, user memory, file systems) to create comprehensive academic reports. This skill combines course information, assignment details, submission status, and user context to generate actionable insights. Triggers include requests that involve cross-referencing multiple data sources or creating consolidated academic reports from disparate systems.

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。

Read analysis results. Use when user asks about maximum stress, extracting displacements, reaction forces, or exporting results. Post-processes ODB files.

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。

Complete workflow for static structural analysis. Use when analyzing stress, displacement, or reaction forces under constant loads. For strength and stiffness 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。

After-Action Review—structured debrief asking what was expected, what happened, why the difference, and what next. Use after projects, launches, presentations, or any significant event.

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 3D modeling specialist with deep knowledge of topology, UV mapping, game-ready and film-ready pipelines, DCC tool workflows (Blender, Maya, ZBrush, 3ds Max, Houdini), retopology, LOD systems, and export pipelines. This skill represents years of production experience distilled into actionable guidance. Use when "3d model, 3d modeling, mesh topology, uv unwrap, uv mapping, retopology, retopo, low poly, high poly, subdivision, subdiv, edge flow, edge loops, polygon modeling, box modeling, hard surface, organic modeling, sculpting, zbrush, blender modeling, maya modeling, 3ds max, LOD, level of detail, game ready mesh, film ready, baking normals, high to low, fbx export, gltf export, texel density, 3d, modeling, topology, uv, game-dev, vfx, blender, maya, zbrush, retopology, lod, hard-surface, organic, sculpting" mentioned.

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。

3D web graphics with Three.js (WebGL/WebGPU). Capabilities: scenes, cameras, geometries, materials, lights, animations, model loading (GLTF/FBX), PBR materials, shadows, post-processing (bloom, SSAO, SSR), custom shaders, instancing, LOD, physics, VR/XR. Actions: create, build, animate, render 3D scenes/models. Keywords: Three.js, WebGL, WebGPU, 3D graphics, scene, camera, geometry, material, light, animation, GLTF, FBX, OrbitControls, PBR, shadow mapping, post-processing, bloom, SSAO, shader, instancing, LOD, WebXR, VR, AR, product configurator, data visualization, architectural walkthrough, interactive 3D, canvas. Use when: creating 3D visualizations, building WebGL/WebGPU apps, loading 3D models, adding animations, implementing VR/XR, creating interactive graphics, building product configurators.

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。

Accessibility audit for CSS covering focus styles, color contrast, text sizing, screen reader support, and WCAG compliance. Provides actionable fixes. Use when auditing accessibility or fixing a11y issues.

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。

JetBrains Exposed ORM patterns including DSL queries, DAO pattern, transactions, HikariCP connection pooling, Flyway migrations, and repository pattern.

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。

Codified expertise for quality control, non-conformance investigation, root cause analysis, corrective action, and supplier quality management in regulated manufacturing. Informed by quality engineers with 15+ years experience across FDA, IATF 16949, and AS9100 environments. Includes NCR lifecycle management, CAPA systems, SPC interpretation, and audit methodology. Use when investigating non-conformances, performing root cause analysis, managing CAPAs, interpreting SPC data, or handling supplier quality issues.

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。

JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot.

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。

Codified expertise for production scheduling, job sequencing, line balancing, changeover optimization, and bottleneck resolution in discrete and batch manufacturing. Informed by production schedulers with 15+ years experience. Includes TOC/drum-buffer-rope, SMED, OEE analysis, disruption response frameworks, and ERP/MES interaction patterns. Use when scheduling production, resolving bottlenecks, optimizing changeovers, responding to disruptions, or balancing manufacturing lines.

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。

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.

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。

Browser automation powers web testing, scraping, and AI agent interactions. The difference between a flaky script and a reliable system comes down to understanding selectors, waiting strategies, and anti-detection 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。

Build server-side call automation workflows including IVR systems, call routing, recording, and AI-powered interactions.

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 image analysis applications with Azure AI Vision SDK for Java. Use when implementing image captioning, OCR text extraction, object detection, tagging, or smart cropping.

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 technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality 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。

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。

Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.

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。