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概要と使いどころ
Establish naming rules for components, tokens, and layers with patterns and worked examples. Use when names are inconsistent or being set. For what the tokens actually contain, use `design-token`.
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Adds user authentication to web and mobile apps with Amazon Cognito (user pools and identity pools) and the AWS Amplify client auth libraries. Covers sign-up/sign-in flows and the login page (Cognito-hosted UI / managed login), MFA, password policies, OAuth 2.0 / OIDC flows (auth-code + PKCE, client credentials), social/SAML federation, tokens (ID/access/refresh, rotation, revocation, storage), Cognito Lambda triggers, identity pools (temp AWS creds), and gating API Gateway (or ALB) routes to signed-in users via Cognito/JWT authorizers. Applies when adding a login or sign-up page, configuring a user pool or app client, choosing user pool vs identity pool, wiring social/SAML, refreshing tokens, requiring sign-in on an API Gateway or ALB, or debugging redirect_uri/token/MFA/CORS/federation errors. Does NOT cover Amplify Gen2 backend definitions (defineAuth, npx ampx → aws-amplify), IAM/STS/Identity Center (→ aws-iam), or API Gateway/Lambda resource config beyond the authorizer (→ aws-serverless).
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。
Calculate NFT rarity scores and rank tokens by trait uniqueness. Use when analyzing NFT collections, checking token rarity, or comparing NFTs. Trigger with phrases like "check NFT rarity", "analyze collection", "rank tokens", "compare NFTs".
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。
Audit and harden Anima and Figma tokens for design-to-code pipelines. Use when protecting API credentials, restricting Figma access scope, or hardening CI/CD design automation pipelines. Trigger with: "anima security", "anima token safety", "figma token security".
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。
JWT and OAuth token attack playbook. Use when validating token trust, signing algorithms, key handling, claim abuse, bearer flows, and OAuth account-binding weaknesses.
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。
Keep Figma and code in sync — map the 3-tier DTCG tokens to Figma Variables (collections + modes), sync in either direction, use the Figma MCP when connected, and verify component parity (variants/states). Use when the user wants to push tokens/components to Figma, pull a design into code, set up token↔Variable sync, or check design-code drift.
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。
Detect insecure JWT (JSON Web Token) implementations in a codebase using a two-phase approach: first map all JWT issuance and verification sites to understand the token lifecycle and signing configuration, then check each verification site for exploitable weaknesses such as algorithm confusion, missing signature verification, weak secrets, header injection, and missing claim validation. Requires sast/architecture.md (run sast-analysis first). Outputs findings to sast/jwt-results.md. If no JWT usage is found in Phase 1, Phase 2 is skipped. Use when asked to find JWT, token forgery, or authentication bypass bugs.
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。
Break down Claude Code usage by model family (Opus / Sonnet / Haiku) from the Agent Monitor dashboard — each family's share of tokens, share of cost, and the spots where an expensive model is doing cheap work. Pulls per-model token and cost splits from /api/pricing/cost, current rates from /api/pricing, fleet token totals from /api/analytics, and per-session model assignment from /api/sessions. Use when deciding model routing or whether to downshift work to a cheaper tier.
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 or audit a design system including component library, design tokens, naming conventions, contribution model, and documentation. Use this skill whenever the user wants to build a design system, audit an existing system, define design tokens at the system level, structure a component library, or set up design system governance. Triggers on design system, component library, design tokens, atomic design, atoms, molecules, organisms, design system documentation, Storybook, Figma library, system governance, design contribution model. Also triggers when teams are inconsistent across products and a system is the answer.
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 the user asks to "estimate LLM costs", "count tokens in prompts", "optimize prompt token usage", "compare model pricing", or "reduce LLM API costs".
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。
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
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。
Audit token consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations. Use when the context window is filling up too fast or before adding new components.
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。
隐私标识移除工具。读取结构化文本数据，按用户选择的类别删除或替换邮箱、IPv4 地址、电话号码等文本中的隐私标识。 当用户提到移除邮箱、清洗 IP、替换电话、从文本里剔除隐私 token 等需求时使用此 skill。 它只处理文本中的 token 清理，不做字段级遮蔽，也不负责图片脱敏、音频脱敏、结构化字段加密或假数据生成。
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。
Agent basina token kullanimi takibi, maliyet optimizasyonu, butce limitleri ve ROI analizi. Session ve proje bazinda harcama raporlari. Hangi agent ne kadar token tuketiyor, hangisi verimli, hangisi israf.
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。
Extract component metadata from a Figma design system and generate production-ready QML controls. Use this skill whenever someone wants to turn Figma components into QML files — whether they say "generate components from Figma", "create QML controls based on a design system", "convert Figma components to QML", "build the component library", "extract button/input/checkbox from Figma", or anything similar. Requires design-tokens.json and QML design system singletons to already exist (from the token extraction skill). Uses Figma MCP to inspect components one at a time and maps variants, states, sizing, and token usage to idiomatic Qt Quick Controls 2 patterns. Trigger this skill at the component generation step of any QML design-system workflow.
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。
OpenClaw 系统诊断和性能分析工具。分析 agent 推理耗时、Token 用量、工具调用统计、 Run 时间线、Gateway 重启历史。支持多种模式：批量分析（默认）、实时跟踪（-f）、 摘要统计（-s）、高级诊断（--advanced）。支持多 Agent 过滤。 使用场景：当用户询问 OpenClaw 运行状态、性能瓶颈、推理延迟、Token 消耗、 工具执行统计、错误排查、agent 活动分析时触发。 触发词：诊断、diagnostics、性能分析、推理耗时、token统计、运行状态、 agent分析、工具调用统计、Run详情、Gateway重启。 指令触发：/diag — 直接执行诊断，支持参数透传。
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。
Implement authentication and authorization using @delon/auth. Use this skill when adding login/logout flows, JWT token management, role-based access control (RBAC), route guards, HTTP interceptors, and session management. Integrates with Firebase Auth and custom permission systems. Ensures secure token storage, automatic token refresh, and consistent authorization checks across components and services.
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。
Token holder distribution, concentration metrics, insider detection, and supply analysis for Solana tokens
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。
Token supply dynamics, vesting analysis, inflation modeling, and valuation frameworks for crypto tokens
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。
Deploy and manage projects on Vercel using token-based authentication. Use when working with Vercel CLI using access tokens rather than interactive login — e.g. "deploy to vercel", "set up vercel", "add environment variables to vercel".
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。
Rust-backed Python library for fast genomic token arithmetic and BED processing. High-performance BED I/O, interval set ops (intersect, merge, complement, subtract), region tokenization against a universe, universe construction. Use for preprocessing large BED collections and ML token vocabularies.
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 composable skill modules with hub-and-spoke loading. Use when token budget is tight.
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 CSS transitions for web apps. Use when implementing notification badges, dropdowns, modals, panel reveals, page transitions, card resizes, number pop-ins, text swaps, icon swaps, success checks, avatar group hovers, error state shakes, search/input clear, skeleton loaders, shimmer text, sliding tabs, tooltips, staggered text reveals, card hover tilt, plus-to-menu morph, or accordions. Triggers on "add a transition", "animate the dropdown", "make the modal open smoothly", "swap icon", "page slide", "stagger animation", "open / close transition", "make it animate", "fade between", "success animation", "form error", "shake on invalid", "hover lift", "avatar stack hover", "clear the search", "skeleton loader", "loading shimmer", "shimmer text", "sliding tabs", "segmented control", "tooltip", "reveal text", "tilt card", "3D hover tilt", "cursor glare", "plus to menu", "FAB morph", "accordion", "collapsible", "expand / collapse", "disclosure". Also "motion tokens", "scan for ad-hoc transitions", "replace hardcoded durations with motion tokens", "tokenize my animations", and the commands transitions reveal, transitions review, transitions apply, transitions refine.
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。
Token architecture, component specifications, and slide generation. Three-layer tokens (primitive→semantic→component), CSS variables, spacing/typography scales, component specs, strategic slide creation. Use for design tokens, systematic design, brand-compliant presentations.
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。