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Expert guidance for Next.js Cache Components and Partial Prerendering (PPR). **PROACTIVE ACTIVATION**: Use this skill automatically when working in Next.js projects that have `cacheComponents: true` in their next.config.ts/next.config.js. When this config is detected, proactively apply Cache Components patterns and best practices to all React Server Component implementations. **DETECTION**: At the start of a session in a Next.js project, check for `cacheComponents: true` in next.config. If enabled, this skill's patterns should guide all component authoring, data fetching, and caching decisions. **USE CASES**: Implementing 'use cache' directive, configuring cache lifetimes with cacheLife(), tagging cached data with cacheTag(), invalidating caches with updateTag()/revalidateTag(), optimizing static vs dynamic content boundaries, debugging cache issues, and reviewing Cache Component implementations.

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 blueprint for Godot 4 project organization (feature-based folders, naming conventions, version control). Enforces snake_case files, PascalCase nodes, %SceneUniqueNames, and .gitignore best practices. Use when starting new projects or refactoring structure. Keywords project organization, naming conventions, snake_case, PascalCase, feature-based, .gitignore, .gdignore.

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。

Godot Expert Auditor: Aurelius. Exhaustive never-list enforcement and architectural slap-down for Godot 4.7 projects. Use when auditing signal decay, ObjectDB orphans, typed Array/Dictionary slop, material.duplicate batch breaks, export case-sensitivity, Expression.execute risks, or sector never-lists. Keywords: auditor, Aurelius, never-list, signal decay, ObjectDB orphans, typed Array, export case-sensitivity, instance uniforms, PackedScene.get_state.

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 patterns for migrating 2D games to 3D including node type conversions, camera systems (third-person, first-person, orbit), physics layer migration, sprite-to-model art pipeline, and control scheme adaptations. Use when porting 2D projects to 3D or adding 3D elements. Trigger keywords: CharacterBody2D to CharacterBody3D, Area2D to Area3D, Camera2D to Camera3D, Vector2 to Vector3, collision_layer migration, sprite to MeshInstance3D, 2D to 3D conversion.

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 blueprint for Godot 4 project organization (feature-based folders, naming conventions, version control). Enforces snake_case files, PascalCase nodes, %SceneUniqueNames, and .gitignore best practices. Use when starting new projects or refactoring structure. Keywords project organization, naming conventions, snake_case, PascalCase, feature-based, .gitignore, .gdignore.

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 patterns for migrating 2D games to 3D including node type conversions, camera systems (third-person, first-person, orbit), physics layer migration, sprite-to-model art pipeline, and control scheme adaptations. Use when porting 2D projects to 3D or adding 3D elements. Trigger keywords: CharacterBody2D to CharacterBody3D, Area2D to Area3D, Camera2D to Camera3D, Vector2 to Vector3, collision_layer migration, sprite to MeshInstance3D, 2D to 3D conversion.

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。

Godot Expert Auditor: Aurelius. Exhaustive never-list enforcement and architectural slap-down for Godot 4.7 projects. Use when auditing signal decay, ObjectDB orphans, typed Array/Dictionary slop, material.duplicate batch breaks, export case-sensitivity, Expression.execute risks, or sector never-lists. Keywords: auditor, Aurelius, never-list, signal decay, ObjectDB orphans, typed Array, export case-sensitivity, instance uniforms, PackedScene.get_state.

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。

Analyze images, video, speech, motion, products, and websites; route local vision, audio, depth, tracking, matting, identity, and restoration models; auto-edit, replicate, enhance, caption, voice, assemble, annotate, validate, and export editable Timeline Studio projects and videos. Use for reference-video remakes, filter and repeated-shot reconstruction, subject-aware reframing, clip splitting, source-time speed curves, Color Wheels grading, ramps and holds, person or product cutout, person or object outline, authorized face swap, shot and timing reconstruction, timeline markers, chapters, beat cues, review notes and ranges, supplied or web-sourced footage, AI video platform selection, cleanup, highlights, product promotion, website walkthroughs, image-to-video assisted edits, optical-flow editing, depth-assisted relighting, grayscale depth-video conversion, depth/2.5D/transition finishing, AI voiceover, subtitles, short-form production, .timeline automation, or editor 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。

Configure Temps as an MCP (Model Context Protocol) server so AI assistants can interact with a Temps instance directly -- listing/inspecting projects and deployments, and (when write mode is enabled) triggering deployments with human confirmation. Use when the user wants to: (1) Set up the Temps MCP server, (2) Connect Claude Code/Desktop, Codex, Cursor, VS Code, Windsurf, or Zed to Temps, (3) Add Temps tools to an AI assistant, (4) Test the MCP wizard locally, (5) Manage multiple Temps MCP connections (dev, staging, prod, or several local dev slots) side by side. Triggers: "temps mcp", "configure temps tools", "add temps to claude", "temps ai assistant", "mcp server setup", "mcp add", "test the mcp wizard".

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。

Operate Temps through the pinned `@temps-sdk/cli` package with bunx or npx. Use when the user mentions Temps CLI, `@temps-sdk/cli`, a CLI command, or asks to deploy, configure, inspect, automate, or administer Temps from a terminal. Covers contexts, projects, deployments, environments, services, domains, monitoring, backups, telemetry, browser Performance Insights/Core Web Vitals, Cloud, platform administration, and read-only managed-data browsing. Apply the target-context, secret-handling, confirmation, and verification rules for every agentic CLI operation.

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。

Integrate the Temps Node.js SDKs for server-side platform access, KV storage, and Blob storage. Use when the user wants to: (1) Call the Temps platform API from Node.js (deployments, projects, analytics, session replay, etc.), (2) Use Temps KV (key-value) storage, (3) Use Temps Blob storage for files, (4) Server-side integration with a Temps project, (5) Backend access to Temps resources. Triggers: "temps node sdk", "temps kv", "temps blob", "backend integration", "node.js temps", "@temps-sdk/node-sdk".

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。

Manage, deploy, operate, and instrument applications with Temps. Use this skill whenever the user mentions Temps, `@temps-sdk/cli@0.1.37`, deploying or migrating an app to Temps, projects, environments, services, domains, backups, logs, monitoring, analytics, browser Performance Insights/Core Web Vitals, observability, error tracking, OpenTelemetry, tracing, session replay, or Temps Cloud. Also use it when preparing an application for production on Temps even if the user does not explicitly ask for the CLI. Route to focused references, proactively detect missing observability during create/link/deploy journeys, and use pinned `bunx` or `npx` CLI invocations with explicit target contexts.

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 debugging Godot projects — remote debugger, print techniques, signal tracing, common error patterns and fixes

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 tests for Godot projects — TDD workflow with GUT and gdUnit4, covers both GDScript and C#

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。

Plans new macOS apps or analyzes existing projects. Creates comprehensive planning documents covering architecture, features, UI/UX, and tech stack. Use when planning a new macOS app or auditing an existing one.

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 knowledge for Azure Deployment Environments development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when defining environment.yaml, configuring dev centers/projects, using ADE/Dev CLI, custom images, or CI/CD deployments, and other Azure Deployment Environments related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Dev Box (use azure-dev-box), Azure Managed Applications (use azure-managed-applications), Azure Resource Manager (use azure-resource-manager).

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 knowledge for Azure DevOps development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing org/projects, repos, pipelines, work items, dashboards/analytics, or Azure DevOps Server deployments, and other Azure DevOps related development tasks. Not for Azure Boards (use azure-boards), Azure Pipelines (use azure-pipelines), Azure Repos (use azure-repos), Azure Test Plans (use azure-test-plans).

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。

Monitor external web and social mentions of the operator's active projects - surface what people are discovering, where they're confused, and where to engage

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 conventional commit messages for Java projects. Use when user says "commit", "create commit", "commit changes", or after completing code changes that need to be committed.

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 wants a 3D model, mesh or GLB out of Higgsfield — image-to-3D, multi-view-to-3D, text-to-3D, rigging or animating a mesh, remesh / retopology, retexture, or 3D Body (human shape + pose from one photo) — or mentions 3D Jutsu / Scene Builder 3D (private Blender scene projects built through Python). Also use for a 3D turnaround of a character or prop as a consistent multi-angle reference, or a physical 3D blockout rendered as a staging reference for a video shot. Names that trigger it: generate_3d, sam_3_3d, image_to_3d, multi_image_to_3d, meshy_v7_image_to_3d, tripo_h3_1_image_to_3d, tripo_h3_1_multiview_to_3d, hunyuan3d_v3_image_to_3d, meshy_v6_text_to_3d, hunyuan3d_v3_1_text_to_3d, tripo_3d, 3d_rigging, meshy_v5_remesh, meshy_v5_retexture, sam_3_3d_body, animation_actions, scene_builder_3d_*.

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。

Pre-production story-and-character development for Higgsfield projects — the upstream layer that decides WHAT to prompt before any model runs. Use when the user wants to build a character, design a world, develop a story or premise, create a character sheet / character bible / story bible, lock a visual style or 'visual DNA', plan a multi-shot narrative with consistent characters, or says things like 'help me design a character', 'build the world', 'I need a backstory', 'make this character consistent across shots', 'develop my film/series concept', or 'I keep getting generic AI characters'. Routes the locked outputs into higgsfield-prompt + the right model. Adapted from Higgsfield's official character-design framework by @vavavinca.

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 for implementing TypeScript in projects, including naming conventions, type definitions, and code style. Triggered when writing or refactoring TypeScript code.

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 scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".

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 a team wants to design, audit, or operate an AI Marketing OS — a Brand Hub source of truth, role-based AI projects for leader, content, design, performance, and knowledge, skill chains, ChatGPT plus Claude plus NotebookLM workflows, MCP connectors, a Notion or Drive second brain, ads data loops, SOPs, weekly reviews, and handoffs. Trigger on 'AI marketing OS', 'set up our marketing AI system', 'Brand Hub', 'AI workflow for the team', 'MCP for ads data', 'how do I make AI actually useful for marketing'. Not for — one campaign brief, see `02-campaign-brief-global`; the weekly report, see `07-marketing-report-global`; the brand visual rules, see `46-brand-guideline-global`; the product context file, see `product-marketing-context-global`.

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。