「arr」の検索結果

Take a change through a verdaccio/verdaccio pull request — branch, checks, changeset, title, body, labels, draft-to-ready, then the CI and review rounds after every push, plus the port PRs to other release lines. Use when opening a PR, after pushing to one, when a check fails, or when review comments arrive.

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。

Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a shareable analytics app', 'deploy my context layer as a web app', 'genbi app', 'wren onboarding', 'wren usage', 'wren generate mdl', 'wren dlt connector', 'wren enrich context', 'wren genbi'.

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。

Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished, submission-ready PDF. Use when user says \"写论文全流程\", \"write paper pipeline\", \"从报告到PDF\", \"paper writing\", or wants the complete paper generation workflow.

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。

Workflow 3: Full paper writing pipeline that goes from a narrative report to a polished, submission-ready PDF. Use when user says "写论文全流程", "write paper pipeline", "从报告到PDF", "paper writing", or wants the complete paper generation workflow.

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。

Write and debug spreadsheet formulas (Excel/Google Sheets), pivot tables, and array formulas; translate between dialects; use when users need working formulas with examples and edge-case checks.

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 that added comments, docstrings, and changelog entries document the code rather than narrate the change that produced it

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 an OpenShell sandbox returns policy_denied, mentions policy.local, or needs a narrow network policy proposal.

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。

Find and read mail in Superhuman — the thread where something was said, sent, or promised — by filtering on who, when, and which split before searching by words, reading the thread before answering, and linking the thread behind every claim. Use when the user asks what someone emailed, whether a reply or an invoice ever arrived, what the latest is on a thread, or what is on their calendar.

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。

Operate the user's real desktop apps and windows on macOS, Windows, or Linux. Use when the user asks to open or drive a native app, click or type in a desktop UI, inspect or arrange a window, use their signed-in system browser, or verify an end-to-end GUI flow, including "open Settings and turn on dark mode", "click Save in that window", "what's on screen". Uses an accessibility-first driver (Cua Driver by default, Peekaboo on macOS). Not for Superset's in-app browser pane, headless scraping, or anything an API or CLI can do directly.

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。

Turn a meeting into work — read its Granola notes, extract the commitments that belong to this user, and carry each one out or draft it (a code change, a ticket, a reply) with a trace back to the note. Use when the user says "do the follow-ups from", "implement what we agreed", "make tickets from", or points at a meeting after a sync, planning session, or customer call.

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。

Answer "what did we say, decide, or promise" from Granola meeting notes — narrow to the meetings that can hold the answer, read the notes before the transcript, and cite the meeting behind every claim. Use when the user asks what happened in a meeting, what a customer or teammate said, what was decided or promised, or refers to a call, sync, standup, or demo.

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。

Imports an FBX vehicle into a CARLA source build as a spawnable vehicle.<make>.<model> — checks the FBX carries CARLA's 4-wheel bone rig, imports the mesh, then assembles the vehicle through CarlaTools' VehicleAuthoringLibrary (physics asset with kinematic wheel bodies, retargeted anim blueprint, four configured wheel blueprints, the vehicle blueprint), registers it in VehicleFactory through CARLA's own add_vehicle_to_vehicle_factory.py, and verifies it spawns, drives and steers. Use when the user asks to "add a car/truck/van to CARLA", "import a vehicle FBX", or needs a custom drivable vehicle spawnable from the Python API.

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。

Draws debug overlays in a running CARLA world via world.debug — points, lines, arrows, bounding boxes, and text strings, each with a colour and lifetime. Use when the user asks to "draw/mark/highlight a point or box in the world", "visualise a path/waypoints", "label a location", or "show something on the map for debugging". Shapes are an overlay, not actors.

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。

Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.

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 self-contained HTML visual explanations for systems, code changes, plans, data, and technical concepts. Use for diagrams, architecture overviews, diff or plan reviews, project recaps, comparison tables, slide decks, animated explainers, narrated MP4 videos, and other visual explanations.

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。

Triage an inbound demand letter — extract fields, cross-check the portfolio, assess merit, present response options with a recommendation, and hand off to matter-intake or demand-intake if escalation is warranted. Use when the user says "we got a demand letter", "triage this demand", or shares an incoming demand to evaluate.

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。

Review the IP clauses in an agreement — assignment, ownership, license grants, warranties, indemnities. Use when reviewing IP terms in employment, consulting, SOW, vendor, or licensing agreements, when asked to check the assignment language or license scope, or when an agreement with IP provisions is pasted or attached.

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。

Plans Convex schema and data migrations with widen-migrate-narrow and @convex-dev/migrations. Use for breaking schema changes, backfills, table reshaping, or zero-downtime rollouts.

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把一个概念铸成杂志专题档案——真问题→失败→转折→顿悟→命名, 6 个 layout 模具 + 4 字族对比 + 探案档案细节

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电子杂志 × 电子墨水; 10 个版面 + 5 套调色板 (墨水/靛蓝瓷/森林墨/牛皮纸/沙丘)

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。

Authoring guide for the primary Native SDK app-logic path: TypeScript app cores - Model, Msg, update, and the pure functions they call, written in the closed app-core subset, checked by the @native-sdk/core frontend, and compiled ahead-of-time to native code by the external core compiler. Use for new apps unless the user explicitly chose Zig, when writing or modifying a src/core.ts app core, fixing subset checker errors (NS1001-NS1069), or deciding how to express state, messages, text (bytes and the byte-text string methods), text input, continuous controls (sliders, scroll), effects (Cmd), subscriptions (Sub), the host-event wiring channels (frameMsg, keyMsg, pinchMsg, dropMsg, appearanceMsg, chromeMsg, envMsgs, app manifest assets), derived values, the view_unbound lint opt-out, local mutation of owned arrays, or how to split a core into modules under src/ (relative imports, namespace imports, @native-sdk/core/text, @native-sdk/core/events). Use ts-services alongside this guide for src/services work.

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Authoring guide for Native SDK TypeScript services under src/services: ordinary scriptc static-tier TypeScript reached through generated typed Cmd clients, shared record shapes, hermetic vendored npm, streaming, deadlines, cancellation, devhost simulation, authority, replay, and the two carriers (in-process thread pool, child subprocess). Use when adding or modifying src/services modules, moving Node/JSON/regex/Map/Date/class work out of a core, or fixing NS1065-NS1067.

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Systematic workflow for auditing TypeScript codebases for import hygiene issues (value vs. type imports, duplicates), missing base class extensions, and incomplete barrel file re-exports, with actionable fix patterns.

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Dashboard panel component pattern for aggregator/summary panels that accept pushed partial data updates via updateData(), defer rendering until first data arrives, and incrementally re-render metrics without re-fetching — ideal for panels that synthesize data already fetched by other panels.

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。