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概要と使いどころ
Technical UI audit — a11y, performance, responsive. Produces a prioritized findings table. Invoke when the user asks for audit on their UI, or mentions 'audit' alongside design / UI / frontend work.
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。
Read, decompose, and analyze IEEE-style papers using routed technical-reading workflows. Use when extracting problem setting, object-method-condition logic, contributions, method pipeline, equations, datasets, baselines, metrics, ablations, limitations, replication details, citation role, related-work positioning, implementation notes, or reviewer-style assessment from a paper, PDF, abstract, or manuscript excerpt.
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。
Review IEEE conference, journal, Transactions, Letters, or magazine manuscripts from a technical reviewer perspective using routed IEEE review gates. Use when evaluating scope fit, novelty, validity, data, clarity, compliance, advancement, engineering significance, method soundness, experiment sufficiency, baseline fairness, figure/table quality, formatting risks, rejection risk, major revision strategy, pre-submission readiness, or the quality and specificity of reviewer comments that may be generic, careless, contradictory, or possibly 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。
Draft, diagnose, and improve IEEE rebuttals, revision plans, cover letters, response letters, and point-by-point replies using routed reviewer-comment handling. Use when responding to IEEE reviewer or editor comments about novelty, scope, method, experiments, baselines, figures, tables, citations, writing, LaTeX formatting, limitations, compliance, technical correctness, or reviewer comments that appear generic, contradictory, unsupported, careless, or possibly 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。
Draft, restructure, and diagnose IEEE-style technical manuscript sections using a routed static/dynamic workflow. Use for IEEE conference, journal, Transactions, Letters, or magazine papers when writing titles, abstracts, introductions, related work, methods, experiments, conclusions, contribution statements, section outlines, or Chinese-to-English engineering paper drafts in AI, computer science, communications, control, signal processing, electrical/electronic engineering, power, robotics, circuits, and applied systems.
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。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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。
Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).
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。
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
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 the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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。
Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).
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 stocks for bullish trends using technical indicators (SMA, RSI, MACD, ADX). Use when user asks to scan for bullish stocks, find trending stocks, or rank symbols by momentum.
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 and best practices for integrating ROS2 systems with web technologies including REST APIs, WebSocket bridges, and browser-based robot interfaces. Use this skill when building web dashboards for robots, streaming camera feeds to browsers, exposing ROS2 services as REST endpoints, or implementing bidirectional WebSocket communication between web UIs and ROS2 nodes. Trigger whenever the user mentions rosbridge, rosbridge_suite, roslibjs, FastAPI with ROS2, Flask with rclpy, WebSocket for robot telemetry, MJPEG streaming, WebRTC for robots, REST API wrapping ROS2 services, web-based robot control, browser robot interface, robot dashboard, CORS configuration for robots, or any web-to-ROS2 bridge pattern. Also trigger for authentication on robot web interfaces, rate limiting sensor streams, video streaming from robot cameras to browsers, or running async web frameworks alongside the ROS2 executor. Covers rosbridge_suite, FastAPI, Flask, WebSocket, and WebRTC approaches.
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。
Project memory workflow for init/upgrade, profile-aware setup, end session, normal/full close, file organization, document archiving, language switching, versioned update logs, rule review, status, wiki sync, and context recovery. Use for /project-butler, setup/初始化, foundation setup, profile setup, end session/收工, normal close, full close, foundation repair, organize files/整理文件, change language/切换语言, continue/接着上次, continue full context/全面回顾, review claude, sync wiki, status. Maintains project memory files. Runs version freshness check before trigger routing.
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。
Creates new Architecture Decision Record (ADR) documents for significant architectural changes using a consistent template and repository-aware naming and storage guidance. Use when a user or agent decides on an architectural change, needs to document technical rationale, or wants to add a new ADR to the project history.
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 wants a summary of what's trending on Product Hunt, Hacker News, Indie Hackers, or other product/startup communities. Also use when the user mentions "what launched today", "trending products", "HN front page", or "keep up with the market".
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 needs to choose between technologies, frameworks, or tools — or says "which framework should I use", "compare X vs Y", "should we migrate from X to Y", "what database should I use", "calculate TCO".
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。
Test a consequential technical assumption with a small, falsifiable experiment before committing to an approach. Use when a plan depends on uncertain runtime, integration, or data behavior that inspection alone cannot establish. Not for preference interviews or routine implementation.
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。
Compress construction schedules using crashing and fast-tracking techniques. Analyze cost-time tradeoffs and find optimal acceleration strategies.
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。
Assess organization's digital transformation readiness. Evaluate data culture, technology adoption, and process maturity.
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。
Technical due diligence for M&A, investment, or acquisition. Reads a target company's codebase and generates a comprehensive tech DD report with architecture assessment, tech debt quantification, scalability analysis, security posture, team capability inference, build system quality, test coverage, deployment maturity, and open source license risks. Outputs tech-dd-report.md formatted like a real investment memo with risk ratings, remediation costs, and go/no-go recommendation.
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 comprehensive API documentation including endpoint descriptions, request/response examples, authentication guides, error codes, and SDKs. Creates OpenAPI/Swagger specs, REST API docs, and developer-friendly reference materials. Use when users need to document APIs, create technical references, or write developer documentation.
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。
Automated code review using ReadLints and Shell for technical 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。
Evaluate technical options with scoring matrix, trigger Gate 4 for significant decisions
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。