171 件 ・ 関連度順
概要と使いどころ
AutoResearch-inspired self-evolution loop for ANY Claude Code skill. Finds flaws, fixes them, benchmarks against a diverse prompt pool (anti-overfitting), and uses blind A/B judging. Fully automated — no human input needed during the loop.
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 patterns for building autonomous coding agents, inspired by [Cline](https://github.com/cline/cline) and [OpenAI Codex](https://github.com/openai/codex).
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 experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.
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。
Practical UI refactoring and visual design review inspired by Refactoring UI by Steve Schoger and Adam Wathan. Use when an AI coding agent needs to improve an existing interface, audit visual polish, redesign a rough UI, review frontend code for hierarchy/spacing/typography/color/depth/image issues, or turn a plain implementation into a cleaner product-quality screen. Do not use for creating UI from scratch, scaffolding a new app, building a new landing page, or designing a new design system unless the user explicitly asks to review or refactor an existing interface.
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。
Time-travel debugging for DAG executions. Inspect agent state at any node, replay decisions with modified inputs, compare execution traces side-by-side, and identify where reasoning diverged. Inspired by LangGraph Studio's state-editing model and Temporal's event history. Activate on "debug DAG", "replay execution", "time travel debug", "inspect node state", "what went wrong at step", "compare runs", "execution diff". NOT for live monitoring (use dag-runtime + websocket-streaming), failure analysis (use dag-ops), or general code debugging.
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。
Universal desktop application controller for Windows. Automate any desktop app — send messages, click buttons, type text, take screenshots, and interact with native Windows applications. Use this skill when the user asks to: "control my computer", "automate desktop", "send a message on [any chat app]", "click on [something]", "type into [app]", "take a screenshot", "操控电脑", "自动化桌面", "给某某发消息", "打开某某软件", "截个屏", or any task involving interacting with Windows desktop applications. WeChat triggers: "send a WeChat message", "message someone on WeChat", "打开微信发消息", "给某某发微信", "微信发送", "微信发消息", "用微信发", "帮我发微信". Email/Web triggers: "打开邮箱", "发邮件", "send email", "open browser", "操控浏览器", "网页操作". Supports: WeChat, WeCom, DingTalk, Feishu/Lark, QQ, Telegram, Slack, Teams, any browser-based web app, and any other Windows desktop application. Inspired by OpenAI's playwright-interactive skill, combining code-based automation with visual screenshot feedback loops. ROUTING: For web/Electron apps (email, Slack, browser), prefer Playwright with CSS selectors for speed and precision. For native desktop apps (WeChat, QQ, DingTalk), use Win32 API automation.
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 building or modifying SwiftUI views, settings windows, menu-bar UIs, or any surface for the KIKA app — or any calm, premium app you want to feel the same way. Encodes the KIKA Design System v2 (June 2026) — a calm, premium, modern dark UI with first-class light mode, inspired by Cursor, Linear, and high-quality dev tools — that you can adopt or adapt for your own app. Apply it to keep color, typography, spacing, and component styling consistent.
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。
Solves complex, open-ended problems using an evolutionary search mechanism inspired by genetic algorithms. Generates a diverse population of candidate answers, scores them against a rubric, then iteratively applies selection, crossover, and mutation to breed progressively better solutions. Use this skill whenever the user wants to explore a solution space deeply, asks for the "best" answer to a subjective or multi-dimensional problem, wants to evaluate competing approaches and distill the strongest, or uses any of these triggers: "evolutionary search", "genetic algorithm", "evolve an answer", "breed solutions", "population-based search", or phrases like "give me multiple approaches and refine the best one". Also trigger when the problem is complex, open-ended, or has no obvious single correct answer and the user wants a high-quality, well-explored result, not just a quick response.
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 experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code spe...
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 patterns for building autonomous coding agents, inspired by [Cline](https://github.com/cline/cline) and [OpenAI Codex](https://github.com/openai/codex).
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 self-contained HTML/CSS benchmark and comparison charts in an ego-inspired Browser-Native Editorial style. Use for blue-white product metrics, model benchmarks, A/B comparisons, efficiency reports, difficulty breakdowns, and compact technical data panels.
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。
Product-discovery coach for Fishbowl engineers — inspired by Marty Cagan's work (never impersonates him). Stage-routes between opportunity brief, research, PRD, ticket drafting, and outcome review. Triggers on "product coach", "help me with product", "I need to write a PRD", "I want to do discovery", "opportunity assessment", "who is this for", "why are we building this", or when an engineer is starting, resuming, or post-mortem-ing product-adjacent work. Invoke with a short description of what you want to do, or invoke bare to be surveyed and routed.
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 Karpathy-inspired coding behavior guidelines — think before coding, prefer simplicity, make surgical changes, and execute toward verifiable goals. Reduces wrong assumptions, overengineering, and unintended side-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。
Knowledge graph and smart memory management using graphify + Obsidian-inspired patterns. Use when: setting up a knowledge graph, managing memory health, cross-linking notes, compiling wiki pages from scattered notes, adding structured frontmatter, or running memory health checks. Triggers on: 'knowledge graph', 'graphify', 'wiki', 'cross-link', 'memory health', 'frontmatter', 'compile notes', 'wikilinks'.
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。
Production-ready patterns for building LLM applications, inspired by [Dify](https://github.com/langgenius/dify) and industry best practices.
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。
Production-ready patterns for building LLM applications, inspired by [Dify](https://github.com/langgenius/dify) and industry best practices.
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。
Patterns for automating GitHub workflows with AI assistance, inspired by [Gemini CLI](https://github.com/google-gemini/gemini-cli) and modern DevOps practices.
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。
Fast, modern JavaScript/TypeScript development with the Bun runtime, inspired by [oven-sh/bun](https://github.com/oven-sh/bun).
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 patterns for building autonomous coding agents, inspired by [Cline](https://github.com/cline/cline) and [OpenAI Codex](https://github.com/openai/codex).
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。
Discover conserved quantities and symmetries from trajectory data. Identifies energy, momentum, angular momentum, and custom invariants using neural networks and symbolic methods. Inspired by Noether's theorem.
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 patterns for building autonomous coding agents, inspired by [Cline](https://github.com/cline/cline) and [OpenAI Codex](https://github.com/openai/codex).
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。
Monospace-driven, matrix-inspired design with high-contrast elements, compact density, and a hacker-chic aesthetic.
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。
Game-inspired fantasy aesthetic with bold, premium visuals, rich color palettes, and immersive thematic elements.
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。
Retro arcade-inspired design with pixel fonts, dotted borders, playful high-contrast colors, and 8-bit game aesthetics.
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。