「space」の検索結果

Per-program stopover rules for award redemptions. Which programs allow free stopovers, how many, how long, and which don't. Covers Icelandair, Aeroplan, Alaska, Flying Blue, Singapore, Cathay, JAL, and the negative space (BA, AA, Delta).

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Use when building any Flutter screen or component to choose responsive Row, Column, Expanded, Flexible, and Spacer layouts before fixed-size or coordinate-based alternatives.

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。

Build, inspect, update, restore, or share Avibe Show Pages for visual explanations, diagrams, reports, or interactive prototypes. Covers the page workspace and its Git history.

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 starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification

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。

Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.

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Archives a completed feature to docs/evolution/, migrates lasting artifacts to permanent directories, and cleans up the temporary workspace. Use after all implementation steps pass and mutation testing completes.

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Use when customers should bring other customers — one-way versus two-way incentives, reward structure and economics, trigger moments, referral messaging, tracking and attribution, fraud controls, and anti-spam compliance by region: TCPA for US, GDPR for EU, PDPA for SEA, LGPD for LATAM. Trigger on 'referral program', 'refer a friend', 'word of mouth', 'viral loop', 'how do I get customers to bring friends', 'affiliate rewards'. Also use when the user has happy customers and no system to use them. Not for — running your own community space, see `28-community-building-global`; posting inside third-party communities, see `38-community-seeding-global`; email flow mechanics, see `14-email-marketing-global`.

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Use when the user wants to show up in OTHER communities without astroturfing — Reddit, Facebook Groups, Discord, Slack, LinkedIn groups, Quora, and niche forums: a prioritized community list with the rules of each space, a named participant roster, post types written in full, reply scripts, a participation calendar, and red lines. Trigger on 'community marketing', 'Reddit marketing', 'seeding plan', 'post in Facebook groups', 'answer questions on Quora', 'we got banned from a group'. Not for — building your OWN paid or private community, see `28-community-building-global`; monitoring mentions across the web, see `15-social-listening-global`; briefing paid creators, see `06-ugc-egc-brief-global`.

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 working with color naming, color theory, color spaces, color definitions, or any task involving color knowledge - palettes, ramps, gradients, conversions, accessibility, perceptual matching, pigment mixing, print-vs-screen color, CSS color syntax, or historical color terminology. Use this skill whenever the user is choosing, comparing, generating, naming, converting, or explaining colors, even if they do not explicitly ask for "color theory."

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 starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification

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。

Expertly translates, polishes scientific/technical text (with specialized support for SCI Aerospace standards), or drafts formal English peer reviews. Ensures accuracy, clarity, and adherence to high academic standards.

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 organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.

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Turn ordinary photos or everyday snapshots into poetic hand-drawn illustrations with large white-paper negative space, vivid localized color, subtle collage accents, and tiny handwritten captions. Use when a user wants a real photo reimagined as an illustration rather than filtered, beautified, or photorealistically edited.

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Generate, derive, optimize, and diagnose structured AI image prompts for luminous cinematic Eastern xianxia environments under one inherited master canon with measurable divine scale, fixed five-layer space, 40–60% content-bearing breathing air, monumental Eastern architecture, railing-free edges, and coherent immortals and costume. Cover one-location scenic landmarks, immense inhabited celestial realms, cloud-borne palace cities, high-key Eastern sky-megastructure imagery, and the explicit `仙界大境原典` creative route. Use for Chinese fantasy scenery, places where immortals live, heavenly capitals, colossal celestial gates, architectural fragments above cloud seas, measurable divine scale, unusual framing, color and lighting direction, style-preserving variants, prompt rewrites, diagnosis, or direct image generation. Support 16:9, 21:9, 4:3, 3:2, 4:5, and 9:16; default to 16:9 for one prompt and never infer a nine-image series from a vertical ratio.

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Swarm intelligence team skill — ACO-driven multi-agent exploration with hybrid LLM coordinator + Python optimization controller. Coordinator generates swarm-config from user task, then runs K iterations of N parallel ants guided by pheromone state. Universal task space via config (nodes + scoring rule). Triggers on "team swarm", "swarm intelligence", "蚁群".

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字符串空格清理工具。读取结构化数据文件（CSV、TSV、Excel等），检查所有字符串类型（object）字段， 删除字段值前后多余的空格，然后输出为相同格式的文件。当用户提到空格清理、去除空格、trim、清理字符串空格等需求时使用此skill。 即使用户没有明确说出"空格清理"，只要任务涉及读取结构化文件并删除字符串字段的前后空格，就应该使用此skill。

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Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.

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Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.

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Use the `hf` CLI for Hub authentication, downloads, uploads, repositories, cache, jobs, buckets, webhooks, and endpoint administration. Use for CLI operations, not model recommendations, paper analysis, training design, or building a Space.

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。

Module composition, state management, workspace strategy, provider versioning, and infrastructure-as-code best practices.

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。

Interactive workspace discovery - learn what tools, workflows, agents, and hooks are available

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CTO-level advisory - build vs buy decisions, tech debt quantification, team scaling, ADRs, technology evaluation (RICE), budget planning, TCO, vendor management, DORA/SPACE metrics

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Instantiate or update a workspace `UNITS.csv` from a selected pipeline and units template (deps/checkpoints/acceptance).

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Execute exactly one eligible Unit in an existing research Workspace; use for stepwise or manual semantic execution when status, Attempt, Artifact, Manifest, checkpoint, and acceptance evidence must remain synchronized.

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。