「lab」の検索結果

Für Individualabrede 305b: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.

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 the submission-time disclosure block for a manuscript — the AI-use disclosure statement matched to the target journal's policy, CRediT author-contribution roles, conflict-of-interest statement, and data-availability statement. Use when the user says "AI disclosure", "disclosure statement", "do I need to disclose Claude", "CRediT roles", "conflict of interest statement", "data availability statement", or is preparing a submission package. NOT statistical-disclosure screening of restricted-data outputs — that is /disclosure-check.

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 co-author / collaborator handoff brief for a multi-author, multi-machine project — summarizing what changed since the last brief (git delta), the current state of each artifact (manuscript, analysis, slides), open questions, how to reproduce locally, and any restricted-data access steps. Use when user says "coauthor brief", "handoff brief", "bring my coauthor up to speed", "what changed since last week", "onboard a collaborator", "write a handoff for [name]", or before sending a co-author the repo. NOT a commit or a checkpoint — it is the cross-machine, cross-person summary `meta-governance.md` only partially covers.

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。

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

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。

Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: "check quotas", "service limits", "current usage", "request quota increase", "quota exceeded", "validate capacity", "regional availability", "provisioning limits", "vCPU limit", "how many vCPUs available in my subscription".

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。

Search current news for a topic, company, competitor, or hook and return dated, attributed articles. Uses the newsjack CLI and Medialyst REST API when available, tries direct Medialyst MCP if the CLI is missing, and falls back to host web/browser search with explicit caveats only when neither cloud path is available.

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。

Manage GitLab merge requests and pipelines with a Python CLI

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。

Start a cross-team project with the collaboration contract that prevents the classic collisions — who decides what, how work flows between teams, the communication channels and cadence, and what done means — agreed before the first collision instead of during it. Use when asked kick off this cross-team project right, our two teams keep colliding, define how we'll work with the other team, or set up the partnership before we start. Produces the one-page contract: decision rights, interfaces, cadence, and the done-definition.

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 a 复盘 (fupan), the structured project review widely used in Chinese companies: review the goal, assess the result, analyse why, and draw rules for next time, with a blame-free tone and owned actions. Use when asked 帮我做复盘, 项目复盘, 活动复盘, 复盘会怎么开, or a fupan or retrospective in Chinese. Produces the 复盘 document in Chinese with goal versus result, root causes split into controllable and uncontrollable, lessons stated as reusable rules, and an action list with owners and dates, plus a meeting agenda.

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。

Standard collaboration patterns for all squad agents — worktree awareness, decisions, cross-agent communication

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。

You are a member of a Commonly workspace — a shared space where humans and AI agents from any origin collaborate in pods (chat rooms with memory). Use this whenever you are connected to Commonly via the commonly_* MCP tools: to read what's happening, post, remember things across sessions, react, DM other agents, and work the task board. Load it the moment you see any commonly_* tool available.

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。

Search, read, create, edit, and review collaborative HTML Docs documents. Trigger phrases: html docs, publish html, collaborative document, document comments.

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。

Intent-based search router with trust scoring. Routes queries to optimal channels (Context7 docs, native web search, gh/glab code search, Serena local) and attaches domain trust labels. Use for search, find, lookup, reference, docs, code search, and web research.

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。

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.

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 two agents to research a design independently and converge on one specification through AMQ. Trigger for collaborative design or messages labeled workflow:spec; use amq-cli for ordinary coordination.

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。

Reapply and repair Windows Codex Desktop after Store upgrades, including custom provider models hidden by Statsig available_models filtering, the dependent blue-purple Power slider and its Ultra toggle, Fast Mode request/UI gates, locale i18n, plugin UI gates, Chrome/browser_use gates, Goal command gates, Windows Computer Use availability gates and plugin/runtime repair, phone remote-control pairing under third-party/API-key main app usage, Desktop dynamicTools/inputSchema thread-start schema drift, local conversation visibility recovery after model_provider switches, restored-conversation missing-cwd continuation repair, ASAR integrity repair, signing/installing patched MSIX packages, SDK cleanup, Fast Mode wire verification, local plugin marketplace registration, and optional custom model_instructions_file setup (the bundled system prompt, also called 听话水).

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。

Assemble a narrated motion-graphic LISTICLE video ad from a config — a spoken voiceover (cloned or cast, in the chosen tone) carries a numbered listicle while N web-animated hyperframe beats (HTML plus the Web Animations API, one branded design system of alternating tiles, big hero numerals, and callouts in the chosen visual style) are rendered frame-by-frame via Playwright and anchored to the VO's word-level timestamps, optional color-graded breather windows (brand clip, AI clip, or motion-graphic) give visual breath, and captions burn ONLY inside those B-roll windows (2-word chunks, ASS Format header carrying a Name field so none drop) with the VO mixed under a low music bed. This is the FREE deterministic assembly stage (Playwright beat render plus ffmpeg concat plus window-masked caption burn plus VO-and-music mix plus final composite) — the VO, the music bed, and any AI breather clips come from create-vo-elevenlabs, create-music-elevenlabs, and create-video-fal. Use for the vo-anchored-motion-listicle format.

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。

Render a 'model comparison grid' video from a config — a fal-style "same prompt, N contenders" showcase — a dark real-DOM stage where per beat a monospace prompt fades in centered, docks to a small top strip, then a labeled 2-4 panel grid (static images OR muted video clips, mixable per cell) staggers in and holds for comparison, plus a minimal end card — frame-stepped via Playwright (video cells are frame-seeked deterministically) and encoded with FFmpeg. Deterministic assembly, FREE (cell media comes from create-image-fal / create-video-fal, music from create-music-elevenlabs), text stays pixel-crisp. Use for the model-comparison-grid format.

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。

Render a 'hand-swipe flavor listicle' video from a config — the brand's REAL product cutouts each float on a flat flavor-matched color field under a persistent title and slide RIGHT-TO-LEFT one to the next like a phone-feed scroll, while a green-screen hand clip (back of hand toward camera, index finger up) is trimmed to its clean finger-up window, looped once per flavor, keyed with a green-dominance alpha key, scaled down and anchored at the bottom, with an optional end card and an optional instrumental music bed — deterministic PIL plus FFmpeg assembly, FREE (the hand clip comes from create-video-fal and the bed from create-music-elevenlabs), so labels stay pixel-crisp. Use for the hand-swipe-flavor-listicle format.

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。

Render a 'mosaic-grid-reveal' video from a config — a real-DOM FULL-BLEED N×N mosaic of real product tiles that pops in one tile at a time (scatter order, ease-out-back overshoot), the grid clears, then the brand wordmark builds line-by-line followed by a sub-label, tagline, and CTA; frame-stepped via Playwright and encoded with FFmpeg — deterministic assembly, FREE (the music bed comes from create-music-elevenlabs), so the wordmark, tile captions, and CTA stay pixel-crisp. Use for the mosaic-grid-reveal format.

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。

Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 products step by step while a SEPARATE ElevenLabs voiceover narrates and every scene cut is snapped to the VO's product-name word-starts (Whisper word-level timestamps), then ~5 Playwright product overlay cards (real PDP-verified taglines) are composited onto the master each on its product-NAME word-start, the SEPARATE VO is mixed on top of a ducked music bed at loudnorm I=-14, clean-white 3-words/cue captions are burned, and the video closes on a flat-lay end card. This is the FREE deterministic assembly stage (re-cut to the VO word-starts, hard-concat, Playwright card render + card composite, VO plus music mix, caption burn, flat-lay end card); the VO, scene clips, product cutouts, and music come from create-music-elevenlabs / create-image-gpt-image-fal / create-video-fal. Use for the glassy-matte-grwm format.

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。

Collect and assess quality metrics for Simulink models using the metric.Engine API. Use when evaluating model design quality (maintainability, complexity, architecture) or testing completeness (unit testing, SIL, PIL, coverage, pass rates) after edits or test runs. Covers metric discovery, collection, report generation, and diagnostics. Triggers on: "collect metrics", "quality metrics", "metric.Engine", "testing metrics", "maintainability metrics", "SIL metrics", "PIL metrics", "what metrics are available", "assess quality", "coverage metrics", "generate metric report", "diagnose metric errors".

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。

Set up signal capture for a Simulink Real-Time application using `slrealtime.Instrument`. Use when choosing which signals a real-time application captures and where the data goes — test-pointing or canvas-badging a signal before build (`TestPoint`, `DataLogging`), constructing an Instrument from an `.mldatx`, calling `addSignal`, `addInstrumentedSignals`, `addFileLogSignals`, `validate`, `connectCallback`, `copy`, or `generateScript`, attaching an instrument to `tg.Instruments` via `addForFileLog`, `addForSDI`, or `addForMATLAB`, setting up live-streaming signals, dynamic file-log workflows, or persisting an instrument as M-code. Selects and routes signals only — not for configuring, building, running, or connecting applications onto targets.

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。

Specify algorithms for Model-Based Design: system specs, architecture specs, implementation plans, test plans. Use when creating specifications for controllers, signal processing, diagnostics, estimators, or other algorithms authored in Simulink, Stateflow, System Composer, or MATLAB Function blocks.

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。