「arm」の検索結果

Fourier analysis specialist covering series, transforms, signal processing, and harmonic analysis

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。

Ideate a brand-new game concept with the user, from a blank page or a one-line hint to a finished CONCEPT card. Use it whenever the user wants to come up with a new game — whether the project has no design document yet, or already has one and they're exploring a fresh idea. Through a structured divergence/convergence dialogue it explores ideas, frames the hook, generates and scores concepts (market validation delegated to /unikit-gd-explore), and settles pillars, loops, motivation, and a pre-mortem. Trigger whenever the user wants to make or invent a game, doesn't know where to start, or gives a genre/theme hint, e.g. "let's come up with a game", "I don't know what game to make", "I want to make a roguelike", "a game about zombies", "a farming game", "help me come up with a concept". For researching or dissecting existing games use /unikit-gd-explore; to write an already-chosen concept as the master GDD use /unikit-gd-spec.

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。

ผู้ช่วยเภสัชกร — drug dictionary (Thai/Generic), interaction matrix, pediatric/geriatric/renal dosing, counseling script สำหรับเภสัชกรที่มีใบประกอบวิชาชีพเท่านั้น

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。

Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.

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。

Clean editorial-style interfaces. Warm monochrome palette, typographic contrast, flat bento grids, muted pastels. No gradients, no heavy shadows.

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。

Give an AI agent its own real browser over MCP tool calls - launch, navigate, click, fill, screenshot, extract text, run JS - with a kernel-level real-device fingerprint and a persistent profile, so the session stays logged in between runs and pages see one coherent device instead of a headless build. No Playwright or SDK code to write. Use when an agent should operate a site itself, when a computer-use / browser-use setup needs a captured real fingerprint rather than a synthetic one, when agent sessions keep losing their login, or when comparing hosted agent-browser services. Also for 'MCP browser', 'browser MCP server', 'let my agent browse the web', 'agent browser control', 'browser-use MCP', 'computer use browser', 'Browserbase alternative', 'Steel browser alternative', 'headless browser detected'. Node (npx) or Python; Windows x64, macOS Intel + Apple Silicon, Linux x64 / arm64. SDK and REST reference is anti-detect-browser; account isolation is multi-account-isolation.

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, build, deploy, and operate production AI agent systems — single agents, multi-agent teams, and autonomous swarms. Complete methodology from agent architecture through orchestration, memory systems, safety guardrails, and operational excellence.

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。

Auto-activate for litestar_mcp, LitestarMCP, MCP, MCPConfig, MCPSkillsConfig, LitestarA2A, A2AConfig, @mcp.tool/resource/prompt, mcp_tool=, or stdio MCP. Not for non-Litestar MCP SDK servers.

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。

Runs a team of 50 LLM personas through a 30-round structured debate to predict market direction. Uses the Canvas Agent Swarm Service — the same shared infrastructure other skills use for smaller agent teams. Output is an influence-weighted consensus direction + trade recommendation with a transparent record of every argument, research query, and cross-examination.

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。

profiling 数据统一采集：远端昇腾采集 NPU 性能数据回传本地，供 profiling-analyze 分析。 两条入口——mindiesd 自家脚本入口（collect_profile.py）与三方框架入口 （collect_patch_template.py 补丁 + torchrun，含 vLLM-Omni HTTP 服务等分场景）； warmup 在 profiler 外（默认 5 步，compile ≥10）。 只要用户想"开 profiler/采 profile/拿算子级数据"，自家脚本或 vllm、LightX2V 等框架都先 用本入口；分析/瓶颈定位/优化选型/并行/基准请求分别属 profiling-analyze、 dit-perf-opt、dit-parallel-opt、benchmark-dev，本入口不承接。 由 model-auto-optimization 的 S1（融合分析）阶段调用，亦由 profiling-analyze 与 dev-workflow 的 采集场景指引加载。

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。

Drafts a U.S. Bill of Sale for transferring personal property ownership from seller to buyer. Covers vehicles, equipment, watercraft, firearms, business assets, and general personal property. Enforces party identification, property description, consideration, condition representations, title warranty, lien disclosure, and jurisdiction-specific execution requirements. Use when drafting a bill of sale, asset transfer document, or ownership transfer instrument.

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。

Expert interior designer with deep knowledge of space planning, color theory (Munsell, NCS), lighting design (IES standards), furniture proportions, and AI-assisted visualization. Use for room layout optimization, lighting calculations, color palette selection for interiors, furniture placement, style consultation. Activate on "interior design", "room layout", "lighting design", "furniture placement", "space planning", "Munsell color". NOT for exterior/landscape design, architectural structure, web/UI design (use web-design-expert), brand color theory (use color-theory-palette-harmony-expert), or building codes/permits.

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。

Applies Gestalt psychology principles to web layout, spacing, grouping, and visual hierarchy. Proximity, similarity, closure, continuity, figure-ground, common fate, Pragnanz — translated into CSS, component structure, and information architecture. Activate on 'gestalt', 'visual grouping', 'proximity spacing', 'visual hierarchy', 'perceptual organization', 'layout psychology', 'whitespace strategy'. NOT for color theory (use color-theory-palette-harmony-expert), not for accessibility auditing (use design-accessibility-auditor).

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。

Expert in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.

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 optimizing Docker builds with BuildKit, designing multi-stage Dockerfiles, leveraging cache mounts, building multi-arch images, choosing distroless vs alpine, or signing images with cosign. Triggers: docker build slow, layer cache not hitting, npm install / pip install reruns, multi-stage final image bloat, glibc vs musl issues, RUN --mount=type=cache, BUILDKIT_INLINE_CACHE, registry cache exporters, qemu emulation for arm64, COPY ordering for cache. NOT for Docker daemon admin, Kubernetes-specific image policies, container security scanning workflows, or Buildpacks (different paradigm).

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。

Apply recognition-primed decision making to agents operating under time pressure, uncertainty, and ambiguous cues. Use for situation assessment, RPD-style action selection, and decision-support design in operational settings. NOT for batch optimization, static planning with full information, or tasks where exhaustive search is cheap and harmless.

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。

Builds comprehensive design systems and design bibles with production-ready CSS. Expert in design tokens, component libraries, CSS architecture. Use for design system creation, token architecture, component documentation, style guide generation. Activate on "design system", "design tokens", "CSS architecture", "component library", "style guide", "design bible". NOT for typography deep-dives (use typography-expert), color theory mathematics (use color-theory-palette-harmony-expert), brand identity strategy (use web-design-expert), or actual UI implementation (use web-design-expert or native-app-designer).

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 designs, color palettes, and UI components for WCAG 2.1 accessibility compliance, providing specific fixes for contrast, touch targets, focus indicators, and screen reader support. NOT for color harmony aesthetics or design system creation.

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。

Choose, compare, and decompose work into the right coordination topology: dag, workflow, manager-driven team, swarm, blackboard, team-builder, or recurring loop. Use when the coordination shape is unclear, when you need topology-native breakdown instructions instead of a generic DAG, or when planning topology and runtime topology may differ. NOT for actual execution, node-level skill matching, or framework/tool installation.

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。

Detects and fixes color contrast violations using WCAG 2.1 guidelines and perceptual analysis. Expert in contrast ratio calculation, color blindness simulation, and providing accessible alternatives. Activate on "check contrast", "color accessibility", "WCAG audit", "readability check", "contrast ratio", "hard to read", "can't see text". NOT for general color theory (use color-theory-palette-harmony-expert), brand color selection (use web-design-expert), or non-visual accessibility (use ux-friction-analyzer).

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。

Expert in ALL computational collage composition: photo mosaics, grid layouts, scrapbook/journal styles, magazine editorial, vision boards, mood boards, social media collages, memory walls, abstract/generative arrangements, and art-historical techniques (Hockney joiners, Dadaist photomontage, Surrealist assemblage, Rauschenberg combines). Masters edge-based assembly, Poisson blending, optimal transport color harmonization, and aesthetic optimization. Activate on 'collage', 'photo mosaic', 'grid layout', 'scrapbook', 'vision board', 'mood board', 'photo wall', 'magazine layout', 'Hockney', 'joiner', 'photomontage'. NOT for simple image editing (use native-app-designer), generating new images (use Stability AI), single photo enhancement (use photo-composition-critic), or basic image similarity search (use clip-aware-embeddings).

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。

Choose multi-agent architectures using environment-first analysis, coordination pressure, commitment tuning, and knowledge levels. Use for autonomy design, protocol choice, and coordination failures. NOT for single-agent planning, centralized schedulers, or prompt-only swarms.

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。

Identifies differential m6A methylation between conditions from MeRIP-seq paired IP/input data using exomePeak2 (GC-bias-aware differential via its bam_ip/bam_input control + bam_treated_ip/bam_treated_input treatment arms), QNB beta-binomial, MeTDiff HMM, and RADAR, plus the paired-symmetric edgeR/DESeq2-on-peak-counts route when batch/lot covariates need fixed-effect handling that exomePeak2's API does not accept. Covers paired vs unpaired vs interaction designs, batch confounding and per-lot meta-analysis, the stoichiometry-vs-expression-vs-IP-efficiency confound, and effect-size filtering against under-powered N=2 designs. Use when comparing m6A across two or more conditions, choosing between exomePeak2/QNB/RADAR/MeTDiff for a design, handling batch confounding when exomePeak2's API is too rigid, distinguishing real hyper/hypo-methylation from expression shifts, applying effect-size thresholds, or planning orthogonal stoichiometry validation (GLORI/SAC-seq/m6Anet mod_ratio).

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。

Tests genotype-environment associations and identifies adaptive loci while correcting for the four-confound landscape (structure, demography, background selection, sampling design) using LFMM2 with mandatory K via sNMF cross-entropy elbow (LEA 3), BayPass Core/AUX/C2/IS with Omega covariance matrix, RDA / pRDA for polygenic adaptation (Forester 2018; requires imputed genotypes), OutFLANK with trimmed FST null, pcadapt, gradient forests (Ellis-Smith-Pitcher 2012, NOT mis-cited Ellis-Manel), Capblancq & Forester 2021 RDA Swiss-army-knife, genomic-offset prediction with Lind & Lotterhos 2025 three-regime caveat, Lotterhos-Whitlock sampling optima, Wang & Bradburd 2014 IBD vs IBE, and Circuitscape + ResistanceGA. Use when identifying adaptive loci across gradients, choosing K for LFMM2, deciding among GEA methods, predicting maladaptation with the novel-environment caveat, distinguishing IBD vs IBE, or optimizing sampling design.

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。