1.8万 件 ・ 関連度順
概要と使いどころ
Add moments of joy, personality, and unexpected touches that make interfaces memorable and enjoyable to use. Elevates functional to delightful. Use when the user asks to add polish, personality, animations, micro-interactions, delight, or make an interface feel fun or memorable.
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 distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.
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。
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
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。
Improve interface resilience through better error handling, i18n support, text overflow handling, and edge case management. Makes interfaces robust and production-ready. Use when the user asks to harden, make production-ready, handle edge cases, add error states, or fix overflow and i18n 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。
Add a capability to the CURRENT Convex app — consults the served Convex capability catalog for always-current procedures (billing, crons, auth, agent, search, …); falls back to built-in hosting or @convex-dev component search. TRIGGER when the user runs /add, or asks to add hosting/publishing or any backend capability to an existing Convex app.
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。
Suggest the matching Convex component when the user hand-rolls a pattern it already solves (crons, sharded-counter, rate-limiter, storage, search, presence, workflow, RAG, prosemirror-sync). Passive — suggest after the task, never interrupt. Never install without consent.
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 writing for technical content, social media, and developer documentation. Use when asked to write tweets, LinkedIn posts, blog posts, READMEs, commit messages, feature announcements, or any written content. Optimized to avoid AI 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。
Submit a blog draft to waynesutton.ai. Use when the user says "blog this", "blog to wsai", "send to wsai", "write to wsai", "post this to my blog", "write this up for the blog", "turn this session into a blog post", "turn this session into a blog post wsai", "draft a post about", "wsai draft a post about", or asks to file session notes to waynesutton.ai. Drafts go to a review inbox and are never published without approval.
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 reactive, type-safe, production-grade backends. ALWAYS use this skill when the user asks to build, plan, design, or implement backend features, APIs, data models, server logic, database schemas, web apps, full stack apps, or mobile apps. This includes planning and architecture discussions.
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。
Automate Accelo tasks via Rube MCP (Composio). Always search tools first for current schemas.
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 guidance for reviewing academic manuscripts submitted to journals, particularly in political science, economics, and quantitative social sciences. Use when asked to review, critique, or provide feedback on academic papers, research designs, or empirical strategies. Emphasizes methodological rigor, causal identification strategies, and constructive feedback on research design.
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 code for encapsulation violations. Detects public mutable state, exposed internals, Tell Don't Ask violations, getter/setter abuse, and information hiding breaches.
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 requests information about academic benchmarks, datasets, or research papers, particularly in machine learning, deep learning, or logical reasoning domains. This skill enables systematic research of academic benchmarks by searching web sources, downloading and analyzing arXiv papers, extracting key metadata (number of tasks, training availability, difficulty levels), and compiling comparative summaries. It triggers on requests involving dataset comparisons, benchmark analysis, or academic paper research for table creation.
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。
Automate Abuselpdb tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Abstract tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Abyssale tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Ably tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
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。
Complete workflow for heat transfer analysis - steady-state and transient thermal. Use when user asks about temperature distribution, conduction, convection, or heat flow.
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 and manipulate Abaqus geometry - parts, sketches, extrusions, CAD import. Use for any geometry creation task including box, cylinder, or STEP/IGES import.
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 material properties for FEA models. Use when user mentions steel, aluminum, Young's modulus, elastic, plastic, density, or asks about material properties.
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 and manage Abaqus jobs. Use when user asks to run the analysis, submit the job, execute the model, or generate input file.
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 output requests - field outputs, history outputs. Use when user asks what results to save, output variables, reduce output file size, or history output.
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。