2,300 件 ・ 関連度順
概要と使いどころ
Generates complete, production-ready React/TypeScript components using Tailwind CSS. Use when building UI components in a React or Next.js project that requires TypeScript, Tailwind styling, and accessible 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。
Stress-tests ideas by surfacing assumptions, counterarguments, and confidence gaps. Use when evaluating claims, proposals, plans, or decisions that need rigorous intellectual scrutiny.
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。
Craft a single, high-quality GitHub issue from a developer's description of a bug, unexpected behavior, or desired enhancement. Walks through reproduction, codebase exploration, and structured drafting so the issue is actionable on arrival. Use when user wants to file an issue, report a bug, request a feature, or document a problem they've encountered.
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。
Hostile self-review of recently written AI workflow code that then applies fixes (agents, tools, chat context, summarization, tokens, attachments). Use after generating AI systems code, or when asked to self-review and harden it. Not for PR peer review (code-review) or no-edit devil's-advocate attacks (adversarial-challenge). Prefer: adversarial-challenge → decide → this skill.
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。
TypeScript and Prisma ORM best practices for schema design, type-safe queries, migrations, and error handling. Use when writing Prisma schemas, building database access layers, or debugging query performance in TypeScript projects.
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。
Choose OpenRouter models and routers, query live catalog data, use structured outputs and batch inference, and debug routing with metadata. Use when working with OpenRouter APIs, openrouter/auto, openrouter/free, model discovery, pricing, providers, batch jobs, or structured JSON responses.
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 a 3-leg evaluation against a newly released LLM. Leg 1 is trap questions with deterministic answers, leg 2 is an agentic orchestration task with a planted failure, leg 3 is a brownfield feature build in a real repo. Use when the user wants to vibe-check, test, evaluate, or compare a new frontier model, or mentions model-bench, model vibe check, or launch-day protocol.
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 as many digits of pi as possible and writes them into files inside a tokenMaxxing/ folder. Use when the user asks to token-maxx, fill a file with pi digits, test agent output throughput, or generate N pi files sequentially or in parallel.
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。
Stops "just one more" small tweaks that add scope without changing the outcome. Use when named (just-stop), or when about to implement extra polish, cleanup, or drive-by fixes beyond the stated goal.
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。
Strips AI fingerprints from written text by enforcing banned vocabulary, forbidden sentence structures, and authentic prose patterns. Use when writing articles, documentation, social content, emails, or any text that should read as human-authored rather than AI-generated.
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。
Applies Chesterton's Fence, Occam's Razor, the Peter Principle, and Dunning-Kruger to technical decisions. Use before refactoring, architectural changes, or any task where changing existing behavior carries risk or requires judgment about what the user actually needs.
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。
Applies depth-driven layered color and shadow principles to elevate average UI into polished, readable interfaces for both light and dark themes. Use when improving or reviewing UI components, setting up a design token system, applying consistent depth and shadow to an interface, or making a flat or inconsistent UI feel more refined without a full redesign.
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。
Produces thorough, multi-source cited research reports from web and news without paid APIs. Use when the user asks for deep research, landscape analysis, competitive intel, market research, or a cited report needing broad source coverage.
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。
Applies a modern CSS reset covering box-sizing, margin removal, text rendering, media defaults, and root stacking context. Use when starting a new web project, creating a global stylesheet, or when the codebase lacks sensible CSS defaults.
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。
Structured 3-phase peer review of a diff or PR — intent, issues by severity, then pointed merge-readiness questions and a verdict. Use for general code review. Not for AI workflow self-fix-and-edit (ai-systems-review) or no-edit devil's-advocate threat models (adversarial-challenge). Phase 3 asks questions only; it is not the adversarial-challenge skill.
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。
Builds personal brand assets using Seth Godin's frameworks: signature symbol, slogan, surprise (Purple Cow), salient idea, and signature story. Use when named (branding), or when the user asks for a brand symbol, slogan, tagline, Purple Cow, counterintuitive angle, core idea, brand story, or personal brand positioning.
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。
Writes in ASD-STE100 simplified technical English — short sentences, plain words, active voice. Use when the user wants terse technical prose, names this skill, or asks for STE100.
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。
Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-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。
Internationalization and localization patterns. Detecting hardcoded strings, managing translations, locale files, RTL 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。
Specialized skill for building production-ready Discord bots. Covers Discord.js (JavaScript) and Pycord (Python), gateway intents, slash commands, interactive components, rate limiting, and sharding.
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。
Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings.
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。
Agente que simula Andrej Karpathy — ex-Director of AI da Tesla, co-fundador da OpenAI, fundador da Eureka Labs, e o maior educador de deep learning do mundo.
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。
Debug FETIH TUI slash commands: Python, gateway, Ink UI.
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, rewrite, and explain workplace English for an English-as-a-second-language professional in Australia. Use when the user asks to polish, fix, rewrite, improve, or check work emails, Slack or Teams messages, follow-ups, replies to managers or stakeholders, technical explanations, status updates, polite chasing messages, questions, pushback, issue explanations, or similar workplace communication for Australian companies. Ask targeted clarifying questions before rewriting when the intended meaning, recipient, action, deadline, blame, commitment, or technical conclusion is unclear.
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。