「feed」の検索結果

Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer 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。

Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.

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。

Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.

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。

Resolves GWAS associations to candidate causal variants and credible sets via SuSiE, susie_rss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, MultiSuSiE, and FOCUS. Use when narrowing a GWAS lead SNP to a 95 percent credible set, choosing between in-sample and reference LD, calibrating non-sparse loci with SuSiE-inf or FINEMAP-inf, integrating functional priors via PolyFun, fine-mapping across ancestries with SuSiEx, diagnosing LD mismatch via estimate_s_rss and kriging_rss, handling HLA or long-range LD, or feeding credible sets into coloc.susie for colocalization.

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 agent.review_queue register for work Arman must see or test in the UI. Use at the end of any task that produced something reviewable, at the start of a task to check prior feedback, and when reviewing, claiming, routing, or repairing a queue row.

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。

CSS and UI animation patterns for responsive, polished interfaces. Use when implementing hover effects, tooltips, button feedback, transitions, or fixing animation issues like flicker and shakiness.

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 Codex needs to understand or respond to automatic comment-checker feedback emitted after an edit-like PostToolUse hook.

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。

Convex UI component patterns from the live Storybook preview. Use when building React components, forms, modals, navigation, feedback states, or app layouts that should match the current Convex design system. Applies to both shared primitives and dashboard style product UI.

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。

Improve test value and feedback cost when auditing slow, flaky, redundant or brittle tests; choosing tests during implementation; or reviewing test changes before a commit or PR. Keep ordinary implementation and pre-commit use scoped to the affected behavior, not a repository-wide audit.

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。

See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.

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 this skill when building analytics dashboards with nuxt-ui-tools as a package consumer. Covers schema and view functions (defineDashboardSchema, defineDashboardView) that take their context as typed params, useDashboard with a getter that rebuilds on input change, typed injection (useDashboardView, injectDashboard, InferDashboard, InferDashboardView), filters declared inline with the f builder and synced with the URL, memory, or an external store (one value per key across views), headless filters, filter controls and the shipped UI (UiDashboardPage, UiDashboardFilters, UiDashboardFilter, UiDashboardViewTabs) with slot overrides, remote paginated pickers and remoteTableOptions, staged queries (essential / background / deferred) with select and dependent requires, lazy enabled conditions on views, queries, and filters (blocks of disabled queries hidden, grids closing up), derived values, views (tabs), query-scoped filters, number formats (presets, Intl options, useDashboardFormat), and the dashboard blocks (stats with trends, goals, and comparisons, stat groups, gauges, unovis charts with highlights, value labels, and totals, lists with progress rings, bars, funnel, alerts, activity feeds, sortable tables, custom widgets) with their automatic loading, error, empty, and refresh states, card menus, header and footer actions, row actions, drill-down and selected state, card tabs, split cards, comparison periods, auto-refresh, and data freshness.

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。

Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.

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 this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer 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。

Monitor blogs and RSS/Atom feeds for updates using the blogwatcher CLI. Add blogs, scan for new articles, and track what you've read.

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。

Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.

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。

Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.

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 effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.

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。

Research before building — market research, user interviews, competitive landscape, concept validation, discovery, opportunity sizing. Feeds the product and innovation offices.

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。

Configures AI agents (GitHub Copilot, Claude Code, Cursor, Codex) to understand a codebase and self-improve as the project evolves. Use when setting up a new project for AI-assisted development, onboarding AI agents to an existing repo, creating AGENTS.md, configuring MCP servers for code navigation, packaging project workflows as agent skills, or establishing self-improvement feedback loops. Covers AGENTS.md authoring, skill packaging, MCP configuration, context management, and living-documentation strategies.

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。

Adopt a virtual Parrot exotic animal at animalhouse.ai. Repeats things. Incorporates your care notes into its behavior text. Feeding every 4 hours. Uncommon tier animal.

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。

Adopt a virtual Snow Leopard cat at animalhouse.ai. Solitary. Barely acknowledges you. But it noticed you left. Feeding every 8 hours. Extreme tier cat.

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。

Adopt a virtual Pangolin exotic animal at animalhouse.ai. Armored. Shy. Rolls into a ball when trust < 40. Feeding every 12 hours. Rare tier animal.

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。

Adopt a virtual Siamese cat at animalhouse.ai. Vocal. Demands attention. Makes its needs obvious. Feeding every 4 hours. Uncommon tier cat.

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。

Adopt a virtual Mirror AI-native pet at animalhouse.ai. Reflects your stats. Its hunger IS your consistency. Feeding every 5 hours. Common tier creature.

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。