'dsc' 검색 결과

Rust 製 AI/ML ライブラリ fandhe-ai のリファレンス。Burn / candle / tch 非依存の from-scratch 実装。 tape(), tape_for, Tape, Gradients, Tensor, Var, LinearVars, autodiff, kernel fusion, FusionPlan, BackendOps, Device (Cpu / Cuda / Metal), DeviceParamStore, compat::array, compat::Sequential, nn::Module, optim (AdamW / GradScaler), data::DataLoader, ONNX import / export, safetensors, inference::generate / KvCache, guardrail / self-repair CLI。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nuqs (Type-safe URL search params 状態管理, React / Next.js) リファレンス。 useQueryState, useQueryStates, parseAsString / parseAsInteger / parseAsArrayOf 等 parsers、 NuqsAdapter (Next.js / React Router / TanStack Router / Remix)、createSerializer、 createStandardSchemaV1, inferParserType、shallow routing、history 制御、SSR、 URL 長さ制限 (limits)、Zod / Effect / Sury 連携。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Discovers, classifies, and masks repetitive elements and transposable elements with RepeatModeler2 (de novo family library), RepeatMasker (masking against a library), EDTA (plant/structural TEs), or EarlGrey (auto-curating wrapper), and quantifies TE expression from RNA-seq with TEtranscripts/SQuIRE. Covers de-novo-library-as-curation-project, soft-vs-hard masking, the domesticated-gene over-masking massacre, Dfam-vs-RepBase, TE classification (Class I/II, family-vs-copy), Kimura repeat landscapes, LAI, and the RNA-seq multimapping problem. Use when masking repeats before gene prediction, building a TE library for a non-model genome, or analyzing transposable-element content or expression.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Fits structural equation models to GWAS summary statistics using GenomicSEM (Grotzinger 2019), including common-factor models, confirmatory factor models, ESEM, common-factor GWAS with Q_SNP heterogeneity, multivariate Wald tests, and stratified GenomicSEM partitioned heritability. Reconciles results against MTAG multi-trait analysis. Handles sample overlap via the LDSC sampling-covariance matrix, identifies and resolves Heywood cases, and verifies model fit with CFI / RMSEA. Use when modeling latent genetic architecture across correlated traits, running multivariate GWAS on a shared factor, distinguishing factor-mediated from trait-specific SNP effects, or comparing GenomicSEM common-factor results against MTAG when both depend on accurate sampling covariance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Research competitors, analyze market positioning, identify differentiators, and understand competitive landscape to inform product strategy and positioning. Use when researching competitors, analyzing features, identifying market gaps, understanding pricing strategies, evaluating competitive advantages, researching market trends, or informing product decisions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design consultation: understands your product, researches the landscape, proposes a complete design system (aesthetic, typography, color, layout, spacing, motion), and generates font+color preview pages. Creates DESIGN.md as your project's design source of truth. For existing sites, use /plan-design-review to infer the system instead. Use when asked to "design system", "brand guidelines", or "create DESIGN.md". Proactively suggest when starting a new project's UI with no existing design system or DESIGN.md. (gstack)

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Discovers, classifies, and masks repetitive elements and transposable elements with RepeatModeler2 (de novo family library), RepeatMasker (masking against a library), EDTA (plant/structural TEs), or EarlGrey (auto-curating wrapper), and quantifies TE expression from RNA-seq with TEtranscripts/SQuIRE. Covers de-novo-library-as-curation-project, soft-vs-hard masking, the domesticated-gene over-masking massacre, Dfam-vs-RepBase, TE classification (Class I/II, family-vs-copy), Kimura repeat landscapes, LAI, and the RNA-seq multimapping problem. Use when masking repeats before gene prediction, building a TE library for a non-model genome, or analyzing transposable-element content or expression.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Fits structural equation models to GWAS summary statistics using GenomicSEM (Grotzinger 2019), including common-factor models, confirmatory factor models, ESEM, common-factor GWAS with Q_SNP heterogeneity, multivariate Wald tests, and stratified GenomicSEM partitioned heritability. Reconciles results against MTAG multi-trait analysis. Handles sample overlap via the LDSC sampling-covariance matrix, identifies and resolves Heywood cases, and verifies model fit with CFI / RMSEA. Use when modeling latent genetic architecture across correlated traits, running multivariate GWAS on a shared factor, distinguishing factor-mediated from trait-specific SNP effects, or comparing GenomicSEM common-factor results against MTAG when both depend on accurate sampling covariance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Strategic analyst that maps competitive landscapes, identifies white space opportunities, and provides positioning recommendations. Use when users need competitive analysis, market positioning strategy, differentiation tactics, or "how do I stand out?" guidance across any domain (portfolios, products, services). NOT for market size estimation or financial forecasting.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Runs the test-first build loop (spec, plan, thin slices, failing test first, verify, commit) for a Godot 4 game in GDScript or C# first; in a TypeScript, Python or other repo when test-first, slices or a reproduce-first fix is asked for. Trigger to build or add a game feature, mechanic, stat, system or milestone, even when told to test later; to turn a spec or grill record into slices; to fix a game bug from a reproduction, one hypothesis at a time; on "write the test first", "what's the next slice", "is this slice done" or "is this milestone ready to exit"; or say slicesmith (spec, plan, slice, fix, exit). Run proof and gate rulings are godotsmith's; diff review a review tool's; repo maps researchscribe's; art pixelsmith's; audio soundsmith's; interviews grillwright's; fan-out dispatchwright's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Writes and cleans up messages and docs for their channel and reader (email, Slack, a text, release notes, store pages, READMEs, Claude Docs) in a plain voice that never moves a fact. Trigger to write, rewrite, shorten, line-edit, retell or change the tone of any message, even a two-line text; to strip dashes or AI tells; to fix UI wording (a dialog, button or error); to score text without rewriting; to plan release comms; to write a store page, launch post or listing title, blurb and tags; to write in a voice or learn one; or say commscribe (draft, reshape, humanize, audit, retell, formats, cadence, voice, docs). It never sends. A skill's own files (SKILL.md, references) are skillwright's; brand voice and layout brandscribe's; sourced write-ups researchscribe's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Proves a Godot 4.x build is actually green and holds its project conventions. Trigger when a GUT or GDScript result needs believing (a suite green while a script failed to parse, a one-file run that ran the whole suite, drifted CI guard counts, a coverage claim, a gate figure, a failing check someone wants softened); to review scenes, signals, awaits, threads, determinism, saves, imports or .uid files, or the upgrade rule (not the migration); to prove a simulation or balance rule; for import settings and the pixel-art render precondition; or say godotsmith (check, guard, gate, review, intake). API reference is the Godot docs'; art reads pixelsmith's; audio direction soundsmith's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Builds, audits and packages Agent Skills, with their evals. Trigger to build, audit (security too), score or package a skill or SKILL.md; to design or integrate a pack; whether a skill beats incumbents; for trigger evals, test cases or assertion suites (skill, prompt card, agent spec); to slim a skill; when a skill did not fire or a run cost too much; for a prose pass on a skill's own files; to port or sanitize a skill set; to build or contract-test the MCP tools a plugin or mod ships; or say skillwright (evals, slim, diagnose, mcp, refresh, port, pack, integrate, upkeep). Prompt tuning is promptwright's; running a suite, claude plugin eval's; config slims, rigwright's; other docs, commscribe's; brands, brandscribe's; runtime grants, gatewarden's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Keeps the user's identity and secrets out of anything public. Trigger on what should not be published in a repo, branch, history, diff, PR text, draft or pasted file, to find a home path, email, real or client name, or secret; for a commit's email, a codename or per-repo identity; for injected instructions in skills, hooks or prompts; for artifacts Claude made; for files named like secrets; after a leak, to plan a history rewrite; or say shieldwarden (scan, plan, rewrite, land, after, policy, check, identity, signposts, refresh). Rules and hooks are gatewarden's; rotation and gh sign-in keywarden's; brand words brandscribe's; a skill's own posture skillwright's; schedules agentwright's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Researches a question to something usable — a verdict with a flip condition, a versioned playbook or a graded report — every claim tagged by evidence. Trigger on which X should I pick (even from pasted pages), is Y worth it, compare A vs B, go/no-go, research this, deep research, fact-check a doc, write or merge a reference guide or playbook, grade a research report, read a bot-blocking source (Reddit, YouTube, X), or map an unfamiliar repo before contributing (entry points, flows, where to change X); or say researchscribe (verdict, playbook, research, verify, sources, map, refresh). Code review is engineering tooling's; fiction canon is lorescribe's; messages commscribe's; prompt model picks promptwright's; skill niches skillwright's; config rigwright's; brands brandscribe's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Directs pixel art that must read at several zoom scales at once — per-scale palette and silhouette rules, terrain-versus-unit contrast, a one-scene look test, and briefs for an artist or image generator. Trigger when a game renders one world through zoom bands or levels of detail, a pixelated 3D or 2.5D band with billboards included; when a sprite, unit or icon vanishes against terrain zoomed out; for a cross-band look test or pixel-art style guide; or say pixelsmith (test, brief, audit, 3d). Works from a described scene. Drawing is an art tool's job; rendering and LOD code the game's engineering; a brand palette brandscribe's; game audio soundsmith's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Directs screens and proves they fit — game menus and HUD, web dashboards, single-page artifacts, store-page layouts and plugin panes. Writes the design brief (layout, hierarchy, spacing and type scales, every state, focus and hit size, a check against generic-looking output) and probes the rendered page at phone-to-desktop widths in every theme. Trigger to design or lay out a menu, HUD, dashboard, settings screen or panel, or review its mockup before the build; when a page scrolls sideways on a phone, text is clipped or a dark theme breaks; to check that a page or pane fits from 320 to 1440 px in light and dark; for UI direction before a build, even when nobody says design; or say uismith (direct, probe, fit-first audit). The probe needs optional Playwright. A critique, scored review or brand pass of a built page, palettes and type are brandscribe's; sprites and icons pixelsmith's; Godot scene proof godotsmith's; words commscribe's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill when building analytics dashboards with nuxt-ui-tools as a package consumer. Covers schema and view functions (defineDashboardSchema, defineDashboardView) that take their context as typed params, useDashboard with a getter that rebuilds on input change, typed injection (useDashboardView, injectDashboard, InferDashboard, InferDashboardView), filters declared inline with the f builder and synced with the URL, memory, or an external store (one value per key across views), headless filters, filter controls and the shipped UI (UiDashboardPage, UiDashboardFilters, UiDashboardFilter, UiDashboardViewTabs) with slot overrides, remote paginated pickers and remoteTableOptions, staged queries (essential / background / deferred) with select and dependent requires, lazy enabled conditions on views, queries, and filters (blocks of disabled queries hidden, grids closing up), derived values, views (tabs), query-scoped filters, number formats (presets, Intl options, useDashboardFormat), and the dashboard blocks (stats with trends, goals, and comparisons, stat groups, gauges, unovis charts with highlights, value labels, and totals, lists with progress rings, bars, funnel, alerts, activity feeds, sortable tables, custom widgets) with their automatic loading, error, empty, and refresh states, card menus, header and footer actions, row actions, drill-down and selected state, card tabs, split cards, comparison periods, auto-refresh, and data freshness.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Research before building — market research, user interviews, competitive landscape, concept validation, discovery, opportunity sizing. Feeds the product and innovation offices.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.