「arr」の検索結果

Draw an animated figure (boxes, arrows, moving data) as one self-contained SVG for a GitHub README, PR, issue or blog post. Use when a change or an explanation needs a diagram — how a request flows, what a background job does, what a feature changed — or when the user asks for a diagram, figure, animation or "show it visually". The docs site's own pages use the interactive player instead (see step 4).

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。

Carry state between runs of a scheduled routine using Hindsight memory. Use when creating or editing a routine, to write the recall and retain steps into the routine's own instructions, and at the start and end of every scheduled or event-triggered routine run.

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。

Processes large tabular scientific datasets with Vaex expressions, filtered views, streamed statistics, binned visualizations, and file conversion. Use for larger-than-RAM HDF5, Arrow, CSV, or Parquet analysis, virtual feature engineering, or Vaex ML preprocessing; distinguishes these operations from estimators and conversions that materialize data.

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。

Supports structured what-if scenario analysis for research planning, experimental contingencies, and scientific project decisions. Explores favorable, reference, adverse, wild-card, contrarian, and second-order scenarios with explicit assumptions, evidence, and decision triggers. Use to stress-test a research plan under uncertainty; scenario narratives do not estimate causal effects or calibrated forecast probabilities.

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。

High-performance DataFrame library for Python ETL, analytics, and pandas migration. It supports expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.

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, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

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。

Conducts systematic, scoping, and narrative literature reviews using PubMed, arXiv, bioRxiv, Semantic Scholar, and other appropriate sources. Use for research synthesis, reproducible literature searches, screening, citation checking, or preparing Markdown and PDF reviews. Tracks search coverage, records versus studies, and evidence limitations; supports meta-analysis planning but does not supply a meta-analysis engine.

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。

Retrieves, versions, and publishes scientific datasets with DataLad and git-annex, and captures computational provenance with datalad run, rerun, and containers-run. Use when cloning or fetching data from OpenNeuro, DANDI, datasets.datalad.org, or any DataLad dataset; when a file in a dataset reads as a broken symlink or a small pointer instead of real data; when an analysis needs a machine-readable record of how each output was produced so it can be re-executed; or when publishing a dataset to siblings such as a GitHub repository plus a storage remote. Also use to decide between DataLad and plain Git for a data-carrying repository.

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。

Handles annotated matrices in single-cell analysis, .h5ad and Zarr files, and integration with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

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。

Creates a GitHub PR with a Linear-ticket-prefixed title and a decision-led, narrative description for Prisma 8. Use when the user wants to create a pull request, open a PR, or submit changes for 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。

Review one or more ADRs with fresh eyes (as a team member without prior context), identify narrative and structural issues, then rewrite them. Use when the user asks to review, improve, rewrite, or take a fresh-eyes pass on an ADR or a set of ADRs (Architecture Decision Records).

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。

Asset and IT register: serial, model, condition, assignee, location, purchase value, warranty expiry and return date, as CSV, SQL, JSON Schema or Notion on request. Use for asset audits.

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。

Spectral vector search using graph Laplacian eigenstructure. Use when cosine/L2 similarity misses latent structure in your 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。

Audit pages and user journeys against a declared WCAG scope. Use when identifying keyboard, screen-reader, focus or contrast barriers and planning verified remediation.

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。

Prepare or carry out authorized publication of Apache Airflow changes, including remote checks, pre-push verification, PR creation, and tracking deferred work. Also use when planning these steps or managing contribution issues.

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 preparing the narrative, sources, and design context for a new editable PPTX deck.

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。

Master ES6+ features including async/await, destructuring, spread operators, arrow functions, promises, modules, iterators, generators, and functional programming patterns for writing clean, efficient JavaScript code. Use when refactoring legacy code, implementing modern patterns, or optimizing JavaScript applications.

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。

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

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。

Hands-on workshop — the learner works through the course instead of watching it, with an exercise or a check every couple of pages, short slides that only set up the next task, guiding narration that asks more than it tells, and a closing page where the pieces come together in one small project. Use when the ask is a workshop, a bootcamp session, 「动手」「实操」「练中学」「边做边学」, or a skill the learner is meant to leave holding; also use when the user names this style. Not for a systematic explanatory course (that is `lecture-style`) and not for occupational procedure training with tools and safety gates (that is `vocational`).

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。

The design law of a slide page — canvas geometry, the text height table, the type scale, contrast pairs, spacing rhythm, and which element type carries which content. Load it when patching slide elements one at a time, when a fix is about colour or contrast, when text has to grow or shrink inside a box, when a page feels crowded or empty, or when replacement content needs real rich-text structure. It is the standard `page-clone` and `pro-editing` edit against, not a procedure of its own — those two decide which pages to touch and in what order, this one decides what a good page looks like when you put it back.

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。

The baseline method for building ONE stage — a single classroom — with this runtime. Covers how the plan is settled in conversation, the order the generation tools are called in, how the classroom roster is written, when narration has to be re-synthesized, and what must be true before a stage is called done. Load this before generating or rebuilding any stage from scratch, whatever its subject; it is the floor the topic skills build on, not an alternative to them.

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。

Professional editing of a course that already exists. Use when the user wants to revise, improve, restructure or polish pages the course already has — fix a page, tune a layout, repair a quiz, reword narration, reorder the deck, or raise the quality of the whole course. Not for building a new course from scratch.

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。

PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).

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。

PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.

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。