「critique」の検索結果

以固定的九节结构生成美国司法意见书的详细法学院案件简报：记忆钩子、事实、程序历史、 法官投票、判决要旨、逐意见分析、五个未来适用假设情形、评论和已核实的关键引文。 还构建投票表、跨案件一致性表、基于视角的评论，以及 article、Beamer 和案例教科书章节格式的 LaTeX。 当有人要求简报案件、分析或解释意见、为学生总结决定、从判决要旨生成假设情形、 评论判决、制表法官投票方式，或将案件分析转换为 LaTeX 时使用。触发词包括 "brief this case"、"case brief"、"explain the holding"、"what did the court hold"、 "hypotheticals based on"、"critique this opinion"、"vote table"、"Beamer presentation"、 "chapter brief"，以及在教学情境中对司法意见或最高法院决定的任何引用。 需要网络搜索来核实引文、投票和判决要旨。

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Surfaces architectural friction and proposes deepening refactors (shallow to deep modules). Renders via mk:preview. NOT for debate (mk:party); NOT for plan critique (mk:plan-ceo-review).

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 plan directory (plan.md + phase-*.md) needs a visual review. By DEFAULT this drives the STRUCTURED visual-plan artifact (visual-plan/plan.json) via the mewkit visual-plan CLI — generate if absent, validate, open the local studio (view/edit), and export plan.html from the approved artifact. Pass --static for the legacy prompt-only single-file plan.html template render. Triggers on "render this plan", "visualize the plan", "open the plan studio", "make a shareable plan page", "plan.html". This is the canonical owner of plan-as-visual-review. NOT for plan critique or scope review (see mk:plan-ceo-review / mk:validate-plan), NOT for generic code/diagram/diff visuals (see mk:preview), NOT for live media generation (see mk:multimodal).

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 generating visual artifacts — explanations, diagrams, slides, or diff visualizations. Triggers on "explain X visually", "diagram this", "show as slides", "diff against main". NOT for rendering a plan as HTML (see mk:visual-plan), live media generation (see mk:multimodal), browser QA (see mk:qa), or plan critique (see mk:plan-ceo-review).

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 surfacing architectural friction and proposing deepening refactors (shallow modules → deep modules) for testability and AI-navigability. Triggers on "improve architecture", "find deepening opportunities", "where is this codebase shallow", "architecture review". Emits structured candidates + precise patches; delegates ALL rendering to mk:preview. NOT for diagram/HTML rendering (see mk:preview); NOT for trade-off deliberation (see mk:party); NOT for plan critique (see mk:plan-ceo-review).

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。

Audit an existing UI for usability, hierarchy, accessibility, and conversion problems. Reviews a live URL, screenshot, or codebase against heuristics and reports prioritized issues with fixes. Use when the user says "audit this UI", "what's wrong with this screen", "UX review", "find the problems", "why is this confusing", or has existing interface to critique. Part of the Product Design set. Can drive a browser for live audits.

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Frontend stack decisions, Cloudflare deployment patterns, component systems, and internal tools architecture. Use for framework selection, deployment strategy, design system bridging, shadcn setup. Activate on "frontend architecture", "tech stack", "Cloudflare Pages", "component library", "internal tools", "shadcn setup". NOT for writing CSS (use frontend-developer), design critique (use design-critic), or backend APIs.

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Conversation patterns and interaction protocols for multi-agent systems. Covers request/response, pub/sub, blackboard, delegation chains, debate, critique, consensus, fan-out/fan-in, supervisor-worker, and peer negotiation. Deep analysis of AutoGen conversation patterns, CrewAI delegation, LangGraph state passing, and FIPA-ACL performatives. Teaches how to design what agents say to each other and in what order. Activate on: "agent conversation", "agent protocol", "multi-agent debate", "agent delegation", "supervisor worker pattern", "agent voting", "consensus protocol", "fan-out fan-in", "agent negotiation", "blackboard pattern", "agent dialogue", "conversation topology", "agent handoff". NOT for: wire format or serialization (use agent-interchange-formats), orchestration infrastructure (use agentic-infrastructure-2026), single agent behavior (use agentic-patterns).

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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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Handles batch effects in bulk RNA-seq via design-matrix inclusion (the correct path for DE), ComBat/ComBat-seq for visualization, SVA for unknown latent factors, RUVSeq for negative-control-gene-anchored unwanted variation, and limma::removeBatchEffect for plotting only. Encodes the Nygaard 2016 cardinal sin against testing on a batch-corrected matrix, the choice between SVA/RUVg/RUVs/RUVr, the confounding non-identifiability problem, the single-cell boundary (Harmony/MNN are NOT for bulk), and the Goh 2017 harmonization critique. Use when designing a DE analysis with batch structure, troubleshooting batch-dominated PCA, choosing ComBat vs ComBat-seq, handling unknown batch via SVA, integrating across studies, or deciding when (rarely) to subtract batch.

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Delimits putative species boundaries from molecular data within the de Queiroz 2007 unified-lineage framework using ASAP (Puillandre 2021 successor to ABGD), mPTP C++ (Kapli 2017 successor to bPTP; bPTP is Python NOT R), GMYC single/multi-threshold (Pons 2006; Fujisawa 2013), multilocus BPP v4 with prior calibration from data (NOT defaults; Yang 2015), SNAPP + BFD* for SNP delimitation, DELINEATE (Sukumaran 2021) speciation-process modeling to address Sukumaran & Knowles 2017 PNAS critique that MSC delimits structure not species, integrative-taxonomy congruence (Padial 2010; Carstens 2013), Dsuite for introgression testing before sister claims (Malinsky 2021), and Meyer & Paulay 2005 barcoding-gap-absence caveat. Use when delineating species from DNA barcoding data, resolving cryptic complexes, choosing among ASAP/mPTP/BPP/DELINEATE, calibrating BPP priors, distinguishing introgression from ILS, or applying the Sukumaran-Knowles oversplitting correction.

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Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria. Covers Crameri scientific colormaps, viridis/cividis/magma, Okabe-Ito categorical, ColorBrewer, and the rainbow/jet critique. Use when choosing palettes for heatmaps, scatter, networks, or any encoding where color carries quantitative or categorical meaning.

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Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions), hyperparameter sensitivity, and the well-documented limits of 2D embeddings. Covers PCA biplot/scree/loadings, t-SNE PCA initialization (Kobak-Berens 2019), UMAP n_neighbors/min_dist trade-offs, and the Chari-Pachter 2023 critique. Use when visualizing high-dimensional data — bulk PCA, single-cell embeddings, multi-omics integration projections.

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Capture what someone actually said without contaminating it with your own inference. Invoke when eliciting intent in conversation (design discussion, requirement interview, decision surfacing) and when turning a conversation into a durable record (ADR, decision node, memory entry, spec `## Decisions` row). Enforces quote-before-critique, keeps illustration separate from commitment, and holds interpretation subordinate to verbatim. Prevents the failure where unspecified space is filled by the recorder and then evaluated as if the speaker had specified it.

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Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI 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。

Run the full speckit workflow end-to-end — specify, plan, critique, tasks, implement, review — making all decisions autonomously. Stops before extract; run that manually.

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。

Perform a dual-lens critical review of the specification and plan from both product strategy and engineering risk perspectives before 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。

Run the speckit preparation phases end-to-end — specify, plan, critique, tasks — making all decisions autonomously. Stops before 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。

Adversarial critique — devil's advocate, stress-test, honest teardown ('poke holes', 'be brutal', 'was hältst du davon'); explicit request only. Routine code or design review → code-review.

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。

Audit how a brand is currently expressed across touchpoints and flag drift from its defined tokens, voice, and strategy. Use to inventory and critique an existing brand before changing it.

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Run a two-agent independent review/redteam followed by peer collaboration to produce a consensus superset of findings and enumerated revision requests. Use when Codex 5.5 and Claude Opus 4.7 should first critique a matter independently, then exchange work, synthesize the best combined analysis, and finish with a single agreed revision list.

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Método da Anthropic para treinar IA inofensiva através de auto-aprimoramento. Abordagem em duas fases - aprendizado supervisionado com auto-crítica/revisão, depois RLAIF (RL from AI Feedback). Use para alinhamento de segurança, redução de outputs prejudiciais sem rótulos humanos. Alimenta o sistema de segurança do Claude.

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。

Critically analyze whether a product, repo, skill, plugin, harness, or architecture vision still fits the real application, user intent, implementation, evidence, and likely future direction. Use when asked to assess vision vs application, predict future fit, critique roadmap direction, analyze strategic intent, or decide whether to keep, refine, pivot, or kill a 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。

Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI 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。