3,458 件 ・ 関連度順
概要と使いどころ
YC-style product validation using six forcing questions. Pressure-tests a feature idea before it becomes a requirement — ensuring real demand, a clear wedge, and evidence behind assumptions.
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 changing a rig while it is alive — `rig grow` / `rig expand` / `rig shrink` / `rig launch` / `rig remove` / `rig discover` / `rig bind` / `rig adopt` / `rig attach`. Covers the 4 failure modes (newly created seat lacks queue/startup/role; edges and permissions not updated; adopt/bind succeeds at tmux but not OpenRig identity; shrink/remove leaves stale topology references) and the rule that mutation must work while the rig is active, not just in clean fixtures.
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 configuring `rig watchdog` policies, authoring wake/refocus/alignment-checkpoint messages, or choosing the right intervention level for a stale-owner situation. The 3-level continuity-check stack (wake / refocus / alignment-checkpoint), the discipline that prevents cadence pollution and bureaucracy theater, and the artifact-pool loop-edge pattern for evidence-aware waking.
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。
Gather and distill context from meetings, competitors, regulatory sources, and internal discussions. Produces background.md for a feature and updates shared context docs when new knowledge is discovered.
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 analyzing dated public-equity event paths, probabilities, payoffs, and expected returns. Do not use for generic catalyst lists, risk sizing, hedges, capital structure, covenants, or credit recovery.
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。
Capture conversations and decisions into structured Notion pages; use when turning chats/notes into wiki entries, how-tos, decisions, or FAQs with proper linking.
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 web performance using Chrome DevTools MCP. Measures Core Web Vitals (FCP, LCP, TBT, CLS, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed. Biases towards retrieval from current documentation over pre-trained knowledge.
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 remote MCP (Model Context Protocol) servers on Cloudflare Workers with tools, OAuth authentication, and production deployment. Generates server code, configures auth providers, and deploys to Workers. Use when: user wants to "build MCP server", "create MCP tools", "remote MCP", "deploy MCP", add "OAuth to MCP", or mentions Model Context Protocol on Cloudflare. Also triggers on "MCP authentication" or "MCP deployment". Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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 AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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 AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities. Generates production-ready agent code deployed to Workers. Use when: user wants to "build an agent", "AI agent", "chat agent", "stateful agent", mentions "Agents SDK", needs "real-time AI", "WebSocket AI", or asks about agent "state management", "scheduled tasks", or "tool calling". Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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 sandboxed applications for secure code execution. Load when building AI code execution, code interpreters, CI/CD systems, interactive dev environments, or executing untrusted code. Covers Sandbox SDK lifecycle, commands, files, code interpreter, and preview URLs. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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。
Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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。
Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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 review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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。
Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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 and apply automatic layout strategies for node-link diagrams and connected-node visuals. Use when the user asks how to auto-arrange nodes, reduce line crossings, route edges, avoid overlaps, stabilize layout, or choose graph-layout algorithms for network diagrams, dependency graphs, database schema diagrams, ERDs, state machines, decision trees, flow diagrams, box-and-line editors, or other line-connected nodes.
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 a proto-persona from current research, market signals, and team knowledge. Use when you need a working customer profile before deeper validation.
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。
使用 Yuxi 知识库进行检索、打开文档、文档内定位和查看思维导图。当用户需要基于已配置知识库回答问题、核验资料或引用文档内容时使用此技能。
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。
Your pathfinder for navigating unknown codebases. Investigates with precision, implements surgically, and never assumes — if it doesn't know, it says so. Maintains a .notebook/ knowledge base that grows across sessions, turning every discovery into lasting intelligence. Summons available skills, MCPs, and docs when the mission demands. Use when fixing bugs, implementing features, refactoring, investigating flows, or any development task in unfamiliar territory. Triggers on "fix this", "implement this", "how does this work", "investigate this flow", "help me with this code". Do NOT use for greenfield scaffolding, CI/CD, or infrastructure provisioning.
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。
Search connected Notion pages and databases, verify the relevant sources, and produce concise answers that preserve links and uncertainty.
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。
The first security skill to install after setting up OpenClaw — powered by Tencent Zhuque Lab. Works like an antivirus for your AI environment: audits installed skills, scans skills before installation, and performs a full OpenClaw security health check to prevent data leaks and privacy risks. Backed by Tencent Zhuque Lab A.I.G (AI-Infra-Guard). Use when the user asks to start a security health check or security scan for the current OpenClaw environment, such as `开始安全体检`, `做一次安全体检`, `开始安全扫描`, `全面安全检查`, or `检查 OpenClaw 安全`; also use when the user asks to audit a specific skill before installation, review installed skills for supply chain risk, or investigate whether a skill is safe. Do not trigger for general OpenClaw usage, project debugging, environment setup, or normal development requests. Optional cloud mode: set AIG_CLOUD_LOOKUP=off for zero outbound HTTPS; when enabled, only skill_name, source label, and OpenClaw version are sent to A.I.G (never skill bodies, chats, or workspace files).
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。
Scan any agent skill for security risks before you install or use it. Powered by Tencent Zhuque Lab A.I.G (AI-Infra-Guard). 100% local static analysis — no file contents or credentials leave your device. Compatible with CodeBuddy, Cursor, Windsurf, Claude Code, OpenClaw and more. Triggers on: `这个 skill 安全吗`, `skill 安全扫描`, `检查 skill 安全`, `audit skill`, `scan skill`, `check skill safety`, `analyze skill`, `inspect skill`, `verify skill`, `skill security`, `skill supply chain`. Do NOT trigger for general agent usage, full system health checks, project debugging, or normal development.
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 falling leaves that read as leaves, with each one tumbling on its own axis so it presents a face, thins to an edge, and opens out again, and with its sideways slip driven by that same tumble. Covers the 2-D canvas build and the instanced-3-D variant, where leaves are recycled from, density-versus-count maths, depth layering, colour under a tone-mapped composite, reduced motion, and visibility pausing. Use for autumn maple, sakura petals, blossom, ash, snowfall shapes, or any drifting foliage where a generic particle field reads as confetti.
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 a container-in-container layout system using nested frames. Use an outer centered container with visible vertical boundary lines and corner markers. Inside, place inner containers inset from the edges, each with its own background and rounded frame. Technique: outer container defines global bounds, inner containers use padding to create inset spacing, layered frames (border + background) to separate levels, and consistent spacing between outer frame and inner blocks.
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。