「composition」の検索結果

Analyzes Remotion compositions for performance issues and provides optimization recommendations. Identifies expensive computations, unnecessary re-renders, large assets, memoization opportunities, and architecture improvements. Use when optimizing render times or when asked to "improve performance", "speed up renders", "optimize Remotion video".

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。

Best practices for Remotion - Video creation in React

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Orchestrates translation of motion designer video specifications into working Remotion code by coordinating specialized agents. Acts as pipeline coordinator that delegates to remotion-scaffold, remotion-animation, remotion-composition, and remotion-component-gen. Use when you have a complete VIDEO_SPEC.md and need full Remotion 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。

A comprehensive design operating system synthesized from 10 canonical design books. Covers research, typography, color theory, composition, branding, logo design, storytelling, web design, creative process, and professional practice.

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。

Best practices for Remotion - Video creation in React

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。

Generates walkthrough videos from Stitch projects using Remotion. Downloads screenshots from Stitch screens, builds a Remotion composition with transitions and text overlays, and renders to MP4. Use with stitch-mcp-list-screens and stitch-mcp-get-screen for screen discovery.

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。

Decomposes portfolio risk with factor attribution, idiosyncratic risk, and marginal contribution to risk analysis. Use when decomposing portfolio risk, attributing risk sources, or analyzing factor risk contribution.

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Builds revolving securitization models with replenishment criteria, early amortization triggers, and portfolio composition limits. Use when modeling revolving structures, analyzing credit card ABS, or evaluating asset purchase criteria.

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Structures secondary portfolio construction with vintage diversification, strategy mix, and geographic allocation optimization. Use when building secondary portfolios, managing allocation targets, or optimizing portfolio composition.

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 founding team composition, complementarity, equity split rationale, and execution capability. Use when evaluating founding teams, assessing management risk, or conducting reference 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。

Constructs ROIC decomposition with invested capital measurement, operating return analysis, and value creation vs destruction assessment. Use when analyzing ROIC, building capital return frameworks, or assessing value creation.

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Structures IAC/LPAC design with composition, authority scope, conflict review protocols, and valuation oversight. Use when designing advisory committees, defining LPAC authority, or structuring conflict resolution processes.

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Evaluates market structure dynamics with order book analysis, spread decomposition, and information asymmetry assessment. Use when analyzing market structure, evaluating trading venues, or assessing execution quality.

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Monitors LP base composition with concentration analysis, redemption risk, and re-up probability assessment. Use when analyzing investor concentration, assessing re-up risk, or managing LP base diversification.

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Evaluates board composition, compensation alignment, and governance practices with proxy advisory and institutional investor standards. Use when analyzing governance, evaluating board effectiveness, or assessing shareholder alignment.

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ALIGN for paper figures — draw a method-overview figure as an executable p5.js program that replays its own construction in named stages, exports SVG, and improves through pixel-only cross-model review whose gate is 'explain the method back from the figure alone, and is it worth looking at'. The method sets the relationships the figure must show, the chosen visual identity sets how its marks look, a composition source lends arrangements; the method may be the source's own (意临) or yours in its arrangement (风格迁移). Not for one-shot raster image generation.

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。

ALIGN for paper figures — draw a method-overview figure as an executable p5.js program that replays its own construction in named stages, exports SVG, and improves through pixel-only independent Codex subagent review whose gate is 'explain the method back from the figure alone, and is it worth looking at'. The method sets the relationships the figure must show, the chosen visual identity sets how its marks look, a composition source lends arrangements; the method may be the source's own (意临) or yours in its arrangement (风格迁移). Not for one-shot raster image generation.

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 external specifications through transformation, classification, gap analysis, component discovery, and decomposition. Creates workflow items with classified context.

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。

Analyze specifications and decompose into independent 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。

Increase visual impact, contrast, personality, and compositional confidence when a design feels bland, generic, or too safe. Use when the design needs more energy, confidence, or memorability—not when the real problem is clutter, over-intensity, or micro-detail polish.

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Run all 5 decomposition validators (req-has-module, code-annotation-maps-to-module, visibility-rule-enforcement, anaemic-context-detection, granularity-match) on the project, reporting violations.

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Prevents premature execution on ambiguous requests. Analyzes request clarity using 5W1H decomposition, surfaces hidden assumptions, and generates structured clarifying questions before work begins. Use at the start of any non-trivial task, or when a request could be interpreted multiple ways. Triggers on "뭘 원하는건지", "요구사항 정리", "clarify", "what exactly", "scope", "requirements", "정확히 뭘", "before we start".

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Exposes Claude's reasoning chain as an auditable, decomposable artifact. Quick mode (default) gives assumption inventory + weakest-link in 2 stages. Full mode (--full) adds decision branching, confidence decomposition, and falsification conditions. Triggers on "왜 그렇게 생각해", "reasoning", "근거", "show your work", "어떻게 그 결론이", "trace", "판단 근거", "why do you think that".

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。

OpenAI GPT Image generation and editing (gpt-image-2, 1.5, 1, mini). Text-to-image, mask-based inpainting, multi-reference composition, multi-turn conversational editing via Responses API, streaming with partial images. This skill should be used when generating or editing images via OpenAI's image models, when near-perfect text rendering in images is needed, when mask-based region-aware editing is required, when multi-turn conversational image editing is desired, or when streaming progressive image delivery is needed. Complements nano-banana-pro (Gemini) as a parallel image generation 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。