「forms」の検索結果

Locate BotProfile::Skill in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "BotProfile::Skill" (symbol BotProfile_Skill). This is a VIRTUAL function - resolve the BotProfile::Skill vtable via RTTI and identify the slot, then emit the slot. Verify by xrefs from expected call sites. vtable slots commonly differ between platforms - never assume identical indices. Trigger: BotProfile_Skill, BotProfile::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。

Locate BotProfile::LookAngleDampingAttacking in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "BotProfile::LookAngleDampingAttacking" (symbol BotProfile_LookAngleDampingAttacking). This is a VIRTUAL function - resolve the BotProfile::LookAngleDampingAttacking vtable via RTTI and identify the slot, then emit the slot. Verify by xrefs from expected call sites. vtable slots commonly differ between platforms - never assume identical indices. Trigger: BotProfile_LookAngleDampingAttacking, BotProfile::LookAngleDampingAttacking

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。

Locate BotProfile::WeaponPref in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "BotProfile::WeaponPref" (symbol BotProfile_WeaponPref). This is a VIRTUAL function - resolve the BotProfile::WeaponPref vtable via RTTI and identify the slot, then emit the slot. Verify by xrefs from expected call sites. vtable slots commonly differ between platforms - never assume identical indices. Trigger: BotProfile_WeaponPref, BotProfile::WeaponPref

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。

Three.js scene setup, cameras, renderer, Object3D hierarchy, coordinate systems. Use when setting up 3D scenes, creating cameras, configuring renderers, managing object hierarchies, or working with transforms.

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。

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

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。

Automatically fetch YouTube transcripts, generate structured summaries, and send full transcripts to messaging platforms. Use when a request includes YouTube URLs and needs metadata, key insights, or downloadable transcripts.

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。

Three.js shaders - GLSL, ShaderMaterial, uniforms, custom effects. Use when creating custom visual effects, modifying vertices, writing fragment shaders, or extending built-in materials.

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 blog articles for Qiita and Zenn from GitHub release information. Use when creating release notes or technical articles that follow specific markdown formats with frontmatter. Supports generating articles from release data, creating custom formatted articles, and saving articles to specified repositories for both Qiita and Zenn platforms

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。

Clone a GitHub repository and automatically build a Docker environment for local verification. Creates a verification workspace in WS/, sets up Docker files, launches the environment, and performs health checks.

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。

Convex UI component patterns from the live Storybook preview. Use when building React components, forms, modals, navigation, feedback states, or app layouts that should match the current Convex design system. Applies to both shared primitives and dashboard style product 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。

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。

Performs a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the user mentions polish, finishing touches, pre-launch review, something looks off, or wants to go from good to great.

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。

Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.

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 comprehensive academic research notes with deep literature coverage. Auto-detects language (EN prompt→EN output, TR prompt→TR output). Supports Obsidian markdown and PDF. Performs 8-15 iterative search cycles with 25-50+ sources for comprehensive coverage. Uses footnote citations and visual overviews.

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。

Academic paper search across 14+ scholarly platforms including arXiv, PubMed, Google Scholar, Web of Science, Semantic Scholar, Sci-Hub, and more. Use for literature review, research discovery, and citation management.

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。

AI agent and chatbot patterns including personas, pipelines, and messaging integrations. Use when building conversational agents, creating AI personas, designing insight pipelines, or integrating with Slack/Kakao platforms.

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。

Expert in 2000s-era music visualization (Milkdrop, AVS, Geiss) and modern WebGL implementations. Specializes in Butterchurn integration, Web Audio API AnalyserNode FFT data, GLSL shaders for audio-reactive visuals, and psychedelic generative art. Activate on "Milkdrop", "music visualization", "WebGL visualizer", "Butterchurn", "audio reactive", "FFT visualization", "spectrum analyzer". NOT for simple bar charts/waveforms (use basic canvas), video editing, or non-audio visuals.

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。

Cross-platform development patterns for OneKey. Use when writing platform-specific code, handling platform differences, or working with native/web/desktop/extension platforms. Triggers on platform, native, web, desktop, extension, iOS, Android, Electron, platformEnv, .native.ts, .web.ts, .desktop.ts, .ext.ts, cross-platform, multi-platform.

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。

Documents minimum SDK/OS version requirements for all OneKey platforms. Use when checking platform compatibility, understanding deployment targets, verifying version requirements, or when user asks if their device can run the project. Triggers on minimum version, SDK version, API level, deployment target, platform requirements, iOS version, Android version, Chrome version, Electron version, can I run, environment check, device compatibility, check environment.

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。

Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business 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。

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

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。

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

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 before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.

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 production-ready Web3 applications, smart contracts, and decentralized systems. Implements DeFi protocols, NFT platforms, DAOs, and enterprise blockchain integrations.

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。