デザインのスキル

Agent Skill design knowledge base — mechanisms, philosophy, patterns, pitfalls. Use when: designing new skills, reviewing skill quality, or deciding whether something should be a 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。

Agent 配置設計指南 — 基於 Claude Code 6 個 built-in agent 的逆向分析。Use when: 設計新 agent、優化現有 agent prompt、決定工具/模型配置、撰寫 dispatch prompt。

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Implement Verilog code from an approved design proposal, then lint and simulate

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 a design proposal, documentation, and RTL backbone from a requirement file

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Scan project state to determine phase completion, write flow_status.md, and orchestrate the full RTL design flow from architecture to documentation

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Code review from the Kent Beck Simple Design 4 Rules perspective. God Object splitting, SRP, duplication removal, naming, cyclomatic complexity. Triggered by "kent beck", "simple design", "simplify", "refactoring" ("리팩토링"), "refactor", "god object", "SRP" keywords.

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Source-grounded catalog of dynamic terminal UI/UX patterns in Claude Code 2.1.170 and Codex CLI 0.142.4 — live status lines, spinner verb sets, streaming and progress affordances. Reference for GEODE CLI/REPL UX work.

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A radically minimal, blank-canvas interface built as a pure edge-to-edge surface, with almost no color and typography carrying the visual weight. Black serves as the only filled color, the only divider, and the sole surface tone cards.

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Design, implement, or evaluate GEODE's GEO capability with source-grounded stage diagnosis, frozen measurement contracts, and no-model preflight before live engine runs.

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Agent system design patterns distilled from the OpenClaw codebase. Gateway-centric control, Session Key hierarchy, Binding routing, Lane Queue concurrency, Sub-agent Spawn+Announce, 4-tier automation, Plugin architecture, Policy Chain, Failover strategies. Triggered by "gateway", "session", "binding", "lane", "spawn", "announce", "heartbeat", "cron", "hook", "plugin", "policy", "failover" keywords.

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Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.

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Apply a refined Scandinavian visual system with a neutral black-and-white foundation, restrained sans-serif typography, purposeful product imagery, generous spacing, clear page chapters, and minimal decoration. Use when the user invokes /scandinavian-design or requests a Nordic, monochrome, calm, spacious, restrained, or minimalist interface.

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Select complementary review lenses for a requested multi-perspective review or a high-risk GEODE change. Covers design, agent constraints, gateway operations, and CLI/tool behavior; not a mandatory four-agent gate for ordinary edits.

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app 側のページ実装を `@playlistwizard/ui` へページ単位で移行するための方針。`@/components/ui/*` import の置換、共通コンポーネント化、既存表示差分の抑制、packages/ui 側の variant 設計を伴う作業で参照すること。

General Xero browser automation notes. Use when automating any Xero page with agent-browser — covers non-standard UI patterns, waiting, and dropdown menus.

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。

Validate frontend design in a real browser using the anoa CLI — screenshots, interactive snapshots, responsive, dark-mode and contrast checks.

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Drive a real browser from the command line — open pages, snapshot the interactive elements as refs, click and fill by ref, read text, run JS, screenshot. Use when a task needs a live browser: checking a page renders, walking a login or checkout flow, scraping something that only exists after JavaScript runs, or reproducing a UI bug.

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。

Used by the Developer agent during Phase 8 (Implement) when building web components, pages, or UI features. Provides strict aesthetic guidelines to create distinctive, production-grade frontend interfaces that avoid generic 'AI slop' aesthetics.

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Define la identidad visual de un producto — propone dos o tres direcciones de color y tipografía justificadas por lo que el producto es, las escribe en design/tokens.css y las deja listas para verlas aplicadas en preview.html antes de decidir. Úsalo tras definir el producto y ANTES de prototipar (p. ej. "define la identidad", "qué paleta usamos", "elige los colores del producto"). No construye vistas.

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Genera las vistas estáticas navegables del producto (landing, auth, app, legales, errores y las propias del mapa de pantallas) usando el design system de design/, sin lógica de backend. Úsalo en el paso "prototipar" del sprint de definición o cuando haya que maquetar vistas nuevas (p. ej. "haz el prototipo", "maqueta las vistas", "crea la landing estática").

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Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.

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Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.

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Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.

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Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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。