749 件 ・ 関連度順
概要と使いどころ
Render `.claude/diamonds/active.yml` as the decisions each diamond has recorded, in order, grouped by mode (discovery, delivery). Read-only. Default format Mermaid stateDiagram-v2, drawn by a script. Recommended at the end of `/mycelium:diamond-assess` so every assessment closes with a visual state-of-play. See `${CLAUDE_PLUGIN_ROOT}/engine/render-conventions.md` for shared render fleet conventions.
日本語の概要は準備中です。原文の説明を表示しています。
Render `.claude/canvas/opportunities.yml` as a diagram or structured list. Read-only. Default format Mermaid mindmap. Consults the attribution registry per `${CLAUDE_PLUGIN_ROOT}/engine/render-conventions.md` consent + privacy gate. Second specialist in the render fleet.
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。
Deprecated alias. Use cxc-dev-visualizer.
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 visual explanations and documents. Triggers: diagrams, charts, interactive models, HTML reports, infographics, 시각화, 그려줘, 문서 만들어줘, 보고서, PDF 생성.
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。
Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER when the orchestrator delegates Step 2 or when the user asks to "generate the figures for my paper" or "render the plots from this experiment log".
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 MindNode-inspired mind mapping interfaces — 8 node shapes, 27+ themes, layout algorithms (horizontal, vertical, radial with D3), keyboard shortcuts, focus mode, dual view. React + xyflow/react v12 + Zustand + Tailwind. Triggers on mind map, visual thinking tool, node-based diagram, brainstorm canvas, MindNode.
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 and edit high-quality images using Google's Nano Banana Pro (Gemini 3 Pro Image) AI model. Use this skill when working with AI image generation or editing tasks including (1) Creating images from text prompts with professional quality, (2) Editing existing images with natural language instructions, (3) Multi-turn iterative image refinement, (4) Product photography and marketing visuals, (5) Creating infographics and diagrams with text, (6) Photorealistic and artistic image generation, (7) Batch image generation workflows, (8) Testing and troubleshooting Gemini image generation API. Supports up to 4K resolution, multiple aspect ratios, reference images, and advanced prompting techniques for cinema-quality results.
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 comprehensive ARCHITECTURE.md files following matklad's canonical guidelines — bird's-eye views, ASCII/Mermaid diagrams, codemaps, invariants, and layer boundaries. Triggers on document the architecture, create ARCHITECTURE.md, map this codebase, architectural overview.
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。
Install and configure the putior R package for workflow visualization. Covers CRAN and GitHub installation, optional dependencies (mcptools, ellmer, shiny, shinyAce, logger, plumber2), and verification of the complete annotation-to-diagram pipeline. Use when setting up putior for the first time, preparing a machine for workflow visualization tasks, when a downstream skill requires putior to be installed, or restoring an environment after an R version upgrade or renv wipe.
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 a generative recipe DSL so agents emit small validated JSON documents and ONE audited interpreter renders them all — data, not code. Covers the N-artifacts threshold for choosing a DSL over bespoke code, designing roles as style slots so a single recipe renders unchanged in every output style, the validator gate (compile + bounds + real render in all styles, plus a --fast mode for corpus-wide sweeps), hand-authored seed recipes, and the emergent conventions that keep a corpus of hundreds consistent without per-item steering. Use when many similar artifacts (icons, status badges, diagram nodes, test fixtures) must be generated by agents, when per-item bespoke code is multiplying unreviewable code paths, or when a whole corpus must be re-rendered cheaply into new styles.
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 non-trivial code needs a design, codebase design or architecture needs improving, or one module needs targeted interface narrowing, seams, or testability. Not for diagrams, deploy, or irreversible changes.
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。
Refresh Atlas diagrams from change-watch metadata.
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 polished, code-driven Remotion motion explainers from scripts, narration, subtitles, product specifications, reference videos, UI recordings, diagrams, or abstract concepts. Use for product launches, AI demonstrations, UI interactions, algorithms, scientific principles, electrical systems, data flows, architecture, charts, equations, and concepts best expressed with React, SVG, Canvas, WebGL, or Three.js. Prioritize continuous spatial logic, visible cause and effect, precise interaction states, editable parameters, deterministic rendering, and evidence-backed visual QA.
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。
Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the 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。
This skill should be used when the user asks to "make an isometric animation", "build a 2.5D isometric scene", "create an isometric infographic", "animate an exploded diagram", "do an isometric city/stack build", "show stacked layers in iso", "extrude blocks with depth", or "add a gentle camera drift to an iso scene". Covers CSS 3D transforms, SVG iso planes, and Three.js OrthographicCamera for true 3D iso — no build step.
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。
제안서 도식화 전략 에이전트. 콘텐츠 분석 → 최적 도식 유형 선택 → Mermaid/차트/인포그래픽 코드 생성. 트리거: 도식화, 다이어그램, 차트, 그래프, 인포그래픽, 플로우차트, 타임라인, 매트릭스, 시각화, 도식, visualize, diagram, mermaid
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 creating nonlinear outlines, generating mindmap diagrams for article structure, mapping a knowledge domain visually, or bridging raw ideas into structured options for the user to select from.
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。
図を使ってコードを説明します。コードの動作を説明する時、コードベースについて教える時、または「これはどう動くの？」と聞かれた時に使用します。
Reorganize label-heavy or netlist-like electronic schematics into human-readable functional diagrams with visible local wiring while preserving proven connectivity. Use for schematic readability correction, overlapping wires or symbols, visually floating connectors or support logic, functional-sheet restructuring, bus presentation, layout annotations, or multi-EDA handoff across KiCad, Altium, EasyEDA, EAGLE/Fusion, gEDA/Lepton, SPICE/netlist, and PDF/image sources.
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, audit, or correct an electronic circuit from a product brief, native schematic, netlist, block diagram, or circuit description. Use for architecture and component-function review, power and logic-domain checks, reset and boot sequencing, bus ownership, ratings, timing, protection, safe states, component suitability, circuit bugs, or layout-facing electrical constraints.
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。
Write engaging PR titles and descriptions for any forge (GitHub today; Bitbucket planned). Use when creating or updating PRs. Leads with narrative paragraphs and reaches for lists, tables, and diagrams when content is genuinely structured.
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。
系统架构图绘制。当需要绘制任何系统架构图、云架构设计图、微服务架构图、Serverless架构图、混合云架构图时使用此技能，支持腾讯云及通用架构场景。基于 Draw.io XML 生成 .drawio 文件，支持二次可视化编辑。
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 and edit presentation slide decks (`.pptx`) with PptxGenJS, bundled layout helpers, and render/validation utilities. Use when tasks involve building a new PowerPoint deck, recreating slides from screenshots/PDFs/reference decks, modifying slide content while preserving editable output, adding charts/diagrams/visuals, or diagnosing layout issues such as overflow, overlaps, and font substitution.
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。