「interact」の検索結果

Expert blueprint for sports games (FIFA, NBA 2K, Rocket League, Tony Hawk) covering physics-based ball interaction, team AI formations, contextual input, and match umpire/score authority. Broadcast framing routes to godot-camera-systems. Use when building soccer, basketball, hockey, racing sports, or arcade sports games. Keywords ball physics, magnus effect, formation AI, team tactics, contextual controls, steering behaviors.

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。

Add privacy-aware session recording and replay to React applications using the Temps SDK. Captures user interactions for playback while respecting privacy through input masking, element blocking, and GDPR-compliant consent flows. Use when the user wants to: (1) Add session recording to their app, (2) Implement session replay functionality, (3) Record user sessions for debugging, (4) Add privacy-compliant screen recording, (5) Debug user issues with visual replay, (6) Implement rrweb-based recording, (7) Set up GDPR-compliant session capture. Triggers: "session recording", "session replay", "record sessions", "user replay", "screen recording", "rrweb", "session capture".

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。

Add Temps analytics to React applications with comprehensive tracking capabilities including page views, custom events, scroll tracking, engagement monitoring, session recording, and Web Vitals performance metrics. Use when the user wants to: (1) Add analytics to a React app (Next.js App Router, Next.js Pages Router, Vite, Create React App, or Remix), (2) Track user events or interactions, (3) Monitor scroll depth or element visibility, (4) Add session recording/replay, (5) Track Web Vitals or performance metrics, (6) Measure user engagement or time on page, (7) Set up product analytics or telemetry. Triggers: "add analytics", "track events", "session recording", "web vitals", "user tracking", "temps analytics", "react analytics".

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。

Configure Temps as an MCP (Model Context Protocol) server so AI assistants can interact with a Temps instance directly -- listing/inspecting projects and deployments, and (when write mode is enabled) triggering deployments with human confirmation. Use when the user wants to: (1) Set up the Temps MCP server, (2) Connect Claude Code/Desktop, Codex, Cursor, VS Code, Windsurf, or Zed to Temps, (3) Add Temps tools to an AI assistant, (4) Test the MCP wizard locally, (5) Manage multiple Temps MCP connections (dev, staging, prod, or several local dev slots) side by side. Triggers: "temps mcp", "configure temps tools", "add temps to claude", "temps ai assistant", "mcp server setup", "mcp add", "test the mcp wizard".

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。

CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intelligent workflow 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。

SERP-based semantic topic clustering for content architecture planning. Groups keywords by actual Google SERP overlap (not text similarity), designs hub-and-spoke content clusters with internal link matrices, and generates interactive visualizations. Optionally executes content creation if codex-blog is installed. Use when user says "topic cluster", "content cluster", "semantic clustering", "pillar page", "hub and spoke", "content architecture", "keyword grouping", or "cluster plan".

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 to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," or "free resource." This skill bridges engineering and marketing — useful for founders and technical marketers.

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。

Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

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。

3D chart visualization with Swift Charts using Chart3D, SurfacePlot, interactive pose control, and surface styling — plus a 2D Swift Charts construction reference (marks, axes, selection, SectorMark, scrollable charts). Use when creating data visualizations with Swift Charts.

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。

iPadOS-specific patterns including Stage Manager, multi-window, drag and drop, keyboard shortcuts, pointer interactions, and Apple Pencil support. Use when building iPad-optimized features.

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 WidgetKit widgets for iOS/macOS home screen and lock screen with timeline providers, interactive elements, and App Intent configuration. Use when adding widgets to an app.

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。

App Intents for Siri, Shortcuts, Spotlight, and Apple Intelligence integration including intent modes, interactive snippets, visual intelligence, and entity indexing. Use when implementing Siri integration, App Shortcuts, or Spotlight indexing.

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。

omicsViewer visualizes ExpressionSet (or SummarizedExperiment) in an interactive way. The omicsViewer has a separate back- and front-end. In the back-end, users need to prepare an ExpressionSet that contains all the necessary information for the downstream data interpretation. Some extra requirements on the headers of phenotype data or feature data are imposed so that the provided information can be clearly recognized by the front-end, at the same time, keep a minimum modification on the existin

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。

Statistical and computational method to analyze the co-expression of gene pairs at single cell level. It provides the foundation for single-cell gene interactome analysis. The basic idea is studying the zero UMI counts' distribution instead of focusing on positive counts; this is done with a generalized contingency tables framework. COTAN can effectively assess the correlated or anti-correlated expression of gene pairs. It provides a numerical index related to the correlation and an approximate

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。

Given a matrix of counts (e.g. from featureCounts) and optional information about the genes, this tool performs differential expression (DE) using the limma Bioconductor package and produces plots and tables useful in DE analysis. Interacti

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。

Mass spectrometry (MS) data backend supporting import and export of MS/MS library spectra from MassBank record files. Different backends are available that allow handling of data in plain MassBank text file format or allow also to interact directly with MassBank SQL databases. Objects from this package are supposed to be used with the Spectra Bioconductor package. This package thus adds MassBank support to the Spectra package.

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。

Extensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may export/imp

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 R package supports interactive visualization of multi-channel images and segmentation masks generated by imaging mass cytometry and other highly multiplexed imaging techniques using shiny. The cytoviewer interface is divided into image-level (Composite and Channels) and cell-level visualization (Masks). It allows users to overlay individual images with segmentation masks, integrates well with SingleCellExperiment and SpatialExperiment objects for metadata visualization and supports image do

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。

Data quality assessment is an integral part of preparatory data analysis to ensure sound biological information retrieval. We present here the MatrixQCvis package, which provides shiny-based interactive visualization of data quality metrics at the per-sample and per-feature level. It is broadly applicable to quantitative omics data types that come in matrix-like format (features x samples). It enables the detection of low-quality samples, drifts, outliers and batch effects in data sets. Visualiz

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。

Interactive loop that builds and tunes an AI prompt for evaluating whether a company fits a client's ICP. Run after any list-building skill (disco-like, blitz-list-builder, google-maps-list-builder, prospeo-full-export) to qualify companies before scaling. Iterates batches of 10 companies with user feedback, stops when 2 consecutive rounds have zero corrections, saves the final prompt for reuse. Always uses Claude Code Task sub-agents — never an external API key.

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。

Find people actively engaging with competitor LinkedIn posts. Given a website URL, discovers competitors, fetches their company and employee posts, collects all commenters and reactors, and outputs a deduplicated CSV of engaged prospects. Use when someone wants to find leads from competitor engagement, build outreach lists from LinkedIn activity, or analyze who interacts with competitor content.

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。

Single "start here" orchestrator for new cold email operators. Asks infrastructure-status questions first, then runs /icp-onboarding → /lead-magnet-brainstorm → /campaign-strategy in sequence, producing a consolidated campaign-plan.md. Ends with an interactive menu of next skills branched on whether the user already has domains/inboxes. Use as the very first invocation on any new repo checkout or when onboarding someone to cold email from zero.

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 a user gives or references a webpage URL and wants to extract, reproduce, port, or locally replay a WebGL, WebGPU, Canvas, shader-like, animated background, interactive 3D, or web visual effect. Locks the target rendering surface group, records shader/resource/render graph/timing/input evidence, builds an evidence-matched local baseline, then projectizes it. Do not use for ordinary DOM/CSS page cloning.

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 and build expressive 3D scenes, explainers and interactive models with grounded subject knowledge. Use for 3D creation or edits, including scientific visualization and spatial puzzles.

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。