「ds」の検索結果

Generates Architecture Decision Records (ADR) for PHP projects. Creates structured decision documentation with context, decision, and consequences.

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 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。

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。

Use when writing CS research papers (conference, journal, thesis), reviewing scientific manuscripts, improving academic writing clarity, or preparing IEEE/ACM submissions. Invoke when user mentions paper, manuscript, research writing, journal submission, or needs help with academic structure, formatting, or revision.

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。

Quality assurance review for implementations. Use when reviewing code quality, checking implementation standards, performing QA cycles, or validating feature quality.

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 abstract strategy games with perfect information, no randomness, and strategic depth. Use when designing a board game, exploring abstract strategy games, brainstorming game mechanics, or evaluating game balance. Keywords: board game, game design, strategy, mechanics, balance.

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 in groups, rings, fields, and algebraic structures with applications to cryptography and number theory

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 set up multiple academic courses in a learning management system (Canvas/LMS) from structured data sources. This skill automates the entire workflow extracting course schedules from emails/attachments, matching instructors from CSV files, creating courses, enrolling teachers, publishing announcements with class details, uploading syllabi, enabling resource sharing for instructors teaching multiple courses, and publishing all courses. Triggers include course schedule setup, Canvas/LMS administration, academic term preparation, instructor assignment, syllabus distribution, and multi-course management.

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 ABP Application.Contracts layer scaffolding (interfaces, DTOs, permissions) from technical design. Enables parallel development by abp-developer and qa-engineer. Use when: (1) backend-architect needs to generate contracts, (2) preparing for parallel implementation workflow, (3) creating API contracts before implementation.

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 recommendation letters, reference letters, or award nominations for students, postdocs, or colleagues. Invoke when user mentions recommendation letter, reference, nomination, letter of support, endorsement, or needs help with strong advocacy, comparative statements, or evidence-based character 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。

Define initial conditions and predefined fields. Use when user mentions initial temperature, pre-stress, residual stress, or import from previous 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。

Agent-to-Agent (A2A) protocol implementation patterns for Google ADK - exposing agents via A2A, consuming external agents, multi-agent communication, and protocol configuration. Use when building multi-agent systems, implementing A2A protocol, exposing agents as services, consuming remote agents, configuring agent cards, or when user mentions A2A, agent-to-agent, multi-agent collaboration, remote agents, or agent orchestration.

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 A2UI 0.8 protocol compliant UI code. Use when building agent-driven interfaces, generating JSONL messages for surfaceUpdate/dataModelUpdate/beginRendering, creating forms, lists, cards, or any UI components that render across web/mobile/desktop platforms.

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。

Apply forces and pressures to structures. Use when user asks to apply a force, add pressure, put a load on, or mentions gravity, point loads, or distributed forces.

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。

Implement Agent-to-Agent (A2A) protocol for inter-agent communication. Use for agent discovery, agent cards, task delegation, and multi-agent orchestration. Triggers on "A2A protocol", "agent-to-agent", "agent discovery", "agent card", "multi-agent", "agent delegation", "agent communication", or when implementing spec/api/017-a2a-protocol.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。

Define boundary conditions - fixed supports, displacements, symmetry. Use when user mentions fixed, pinned, clamped, supported, or constrained. Does NOT handle loads or forces.

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。

Implement state machines with AASM for workflow management. Covers state transitions, guards, callbacks, and 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。

[30] ANALYZE. Understand how changes impact the system — what's the core, what's affected, what depends on what. Use when planning changes, analyzing systems, debugging issues, or anytime you need to see the full picture of cause and effect. Triggers on "what's affected", "impact analysis", "dependencies", "scope mapping", or when you need to understand ripple effects.

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。

Library of accessibility personas representing people with various disabilities, impairments, and situational limitations. Use this skill when users ask about disability types, accessibility personas, user needs for specific conditions, how people with disabilities use technology, assistive technology users, or designing for accessibility. Triggers on requests about blindness, deafness, cognitive disabilities, motor impairments, low vision, screen readers, sign language, autism, ADHD, temporary disabilities, or any question about "how would a person with X use this".

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。

Adds comprehensive accessibility testing to CI/CD pipelines using axe-core Playwright integration or pa11y-ci. Automatically generates markdown reports for pull requests showing WCAG violations with severity levels, affected elements, and remediation guidance. This skill should be used when implementing accessibility CI checks, adding a11y tests to pipelines, generating accessibility reports, enforcing WCAG compliance, automating accessibility scans, or setting up PR accessibility gates. Trigger terms include a11y ci, accessibility pipeline, wcag ci, axe-core ci, pa11y ci, accessibility reports, a11y automation, accessibility gate, compliance check.

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。

Adds accessibility annotations (ARIA labels, roles, alt text) to make web content accessible. Use when user asks to "add accessibility", "make accessible", "add aria labels", "wcag compliance", or "screen reader support".

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 in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).

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。