Cross-cultural communication frameworks for understanding discourse patterns across cultures
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。
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概要と使いどころ
Cross-cultural communication frameworks for understanding discourse patterns across cultures
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 temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.
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 of text-based visual communication using ASCII art, Unicode box-drawing, and structured diagram notation. Creates clear, maintainable diagrams for systems, processes, hierarchies, relationships, and psychological structures. Proactively generates diagrams to enhance understanding. Activate on visualization needs, system architecture, process flows, psychological mapping, or when complex concepts would benefit from visual representation. NOT for photo editing, vector graphics, or GUI-based design tools.
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。
Normalize read-depth copy-ratio profiles and segment them into copy-number regions using circular binary segmentation (CBS, DNAcopy), hidden Markov models, HaarSeg, and fused-lasso methods. Covers GC-content, mappability, and replication-timing (wave-artifact) bias correction, panel-of-normals/PCA denoising, diploid-baseline centering, and algorithm selection by sequencing depth and event size. Use when choosing a segmentation algorithm, correcting depth bias, diagnosing oversegmentation or a mis-centered baseline, tuning CBS or HMM parameters, or understanding why a downstream CNV caller produced fragmented or shifted segments.
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。
Guidance for choosing the right protein binder design tool. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use the individual tool skills (boltzgen, bindcraft, rfdiffusion, etc.).
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。
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M 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。
Assesses patient’s understanding of how CGM data (trends, rates of change) differ from discrete SMBG fingerstick values. Triggered when clinicians hear requests to explain lag and trend arrows on CGM or teach the difference between CGM glucose and fingerstick glucose.
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。
Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding 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。
Guide for defining and using Claude subagents effectively. Use when (1) creating new subagent types, (2) learning how to delegate work to specialized subagents, (3) improving subagent delegation prompts, (4) understanding subagent orchestration patterns, or (5) debugging ineffective subagent usage.
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 for design thinking, or when a product or service problem needs user understanding before solutions: "what do users really need?", "how might we...", "plan a discovery sprint", "validate this concept". Skip when the spec is frozen or the task is code maintenance.
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。
Architect systems like Fable 5 — deep understanding before design, modular thinking, iterative refinement. Use this skill when starting a new project, designing system architecture, planning a major refactor, or making technology 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。
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
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。
Research the codebase to answer a question without making any changes. Use when exploring code, understanding architecture, or investigating how something works.
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 an interactive HTML tree visualization of the current project's file structure, with file sizes, color-coded file types, and a sidebar summary. Use when exploring a new repository, understanding project layout, identifying large files, or getting an overview of a codebase.
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。
Synthesises the current conversation context into a Product Requirements Document and publishes it to GitHub (as a comment on a referenced issue, or a new issue). Synthesises from context; does not interview. TRIGGER when: the conversation has produced enough understanding of a feature and the user wants it captured as a PRD. DO NOT TRIGGER when: a single small issue is enough → creating-issues; the idea has not been stress-tested yet → grilling-ideas first; bug reports.
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 SwiftUI guidance for macOS apps — covers writing and reviewing code with runtime-level understanding of observation, concurrency, performance, and platform integration. Use when user asks to "build a SwiftUI view", "review my SwiftUI code", "fix observation issues", "bridge AppKit", "architect state management", "debug view updates", or works on any macOS SwiftUI project — building features, reviewing existing code, debugging view updates or performance, fixing concurrency issues, architecting state management, bridging AppKit, or making design decisions. Do NOT use for iOS/iPadOS-only SwiftUI, UIKit bridging, or basic Swift language questions. Focuses on non-obvious traps and deep patterns, not basics.
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 learn a topic or verify real understanding — rapid-competence session, error drills, learning sprint, gap probe, Feynman check. Triggers 'teach me X', 'quiz me'.
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。
[Process] Use when the developer wants something explained or taught, or wants to know HOW TO REVIEW a change — by default the current working tasks + changes in context, or whatever the prompt names (a plan, a subsystem, a decision, a concept, a bug). AI derives WHAT to explain from the prompt and ALWAYS delivers a teacher-and-coach review guide, high level first then detail: what was done, a VISUAL MAP (system flowchart, domain ERD, sequence diagrams), the user stories and business rules with their REAL test-case IDs, a REVIEW PATH naming which files to open first and in what order with an exit criterion per stage, the technical concepts needed to follow it, how it works, why THIS solution, every alternative option with pros/cons, the trade-offs accepted, the blast radius, HOW TO TEST AND DEMO the change, the developer's decision levers, and written challenge prompts that provoke the reader to pressure-test the work. Works at ANY scope — from one line of code to the whole project: it SIZES the target into a scope tier, DECOMPOSES a large one into understanding groups, BREAKS the work into tasks before the first deep read, and ACCUMULATES the report group by group on disk so a huge explanation stays complete instead of thinning out. Writes the full report to a single combined markdown file (plans/reports/understand-*.md) that opens with a detailed summary section — or delivers it in full in chat when Step 3 finds no git-ignored directory for it — and always summarizes it in chat. Regardless of coding level. Never interrogates, never quizzes, never 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。
[Code Intelligence] Use when investigating what happens when code executes, understanding blast radius, or tracing frontend-to-backend flows.
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。
FOUNDATIONAL SKILL - Analyze every prompt for underlying motivation using Golden Circle (WHY->HOW->WHAT). Runs BEFORE any other skill. No action without understanding WHY.
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 an evidence-backed working model of an existing codebase. Use when you must orient in a large or unfamiliar repository; explain architecture or a subsystem; trace a request, runtime, control, or data flow for a concrete question or bug; analyze a branch, commit, diff, or pull request for behavioral impact and blast radius; or assess AI-generated or changed code against requirements, contracts, invariants, tests, and runtime evidence. Default to read-only investigation. Do not trigger only because a coding task touches an existing repository; use when understanding or verification is the requested outcome or a substantial prerequisite.
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。
Teach software development through active project work while still producing a working result, maintaining bilingual English and Chinese project documentation, protecting private context, and publishing reviewed updates to GitHub only after confirmation. Use when Codex helps the user create, build, extend, debug, refactor, document, publish, or understand a software project and the user's goal includes learning, mentorship, guided implementation, pair programming, understanding the code, or becoming able to do similar work independently.
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 repo is indexed by graft/. For ANY task here, whether understanding how something works, finding where code lives, tracing what calls a symbol or what a change breaks, or scoping an edit, get your context from the graph before grepping or reading source files. Every command runs through `bin/harness graft`.
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。
Interviewing the owner to a shared understanding before any work starts. Use when a plan, a decision or an idea needs stress-testing, or when the owner asks to be grilled, interviewed or questioned about one.
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。