「recipes」の検索結果

Create or edit the active iPolloWork video's visual assets, installed recipes, editable composition and seek-safe motion; use for assembly or local picture/text/theme changes.

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 any ordered process into a data-driven vertical or horizontal scroll story with a base line, progress fill, active step states, responsive collapse, semantic fallback, and reduced-motion behavior. Use for onboarding, checkout, roadmaps, recipes, case studies, service processes, histories, or narratives where progress through the sequence should become visible while scrolling.

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 designing/implementing UI with Tailwind CSS (layout, typography, responsive, theming, component patterns). Includes quick recipes and conventions for clean, consistent web design.

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。

This skill should be used when the user wants to "write agent code", "build an agent with ADK", "add a tool", "create a callback", "define an agent", "use state management" — in a project that needs ADK (Agent Development Kit) API patterns and code examples. It provides a quick reference for agent types, tool definitions, orchestration patterns, callbacks, state management, the graph Workflow API, and reference recipes to study. Do NOT use for scaffolding (use google-agents-cli-scaffold) or deployment (use google-agents-cli-deploy).

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。

Recipes for the lsp tool — resolving where a symbol is defined, every place it is used, type signatures and docs, file outlines, and compiler/type errors through a real language server (Go, TypeScript/JavaScript, Python, Rust). Use when navigating or explaining code by symbol, finding callers or usages, checking what broke after an edit, or deciding between lsp and text search.

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。

Drive tuios from inside one of its panes. Find out where you are running, read and write other panes, run work and wait on it instead of polling, report your own state so the person sees it, and talk to the other agents and the person safely. `tuios --skill <topic>` prints the rest: fleets of agents, turn checkpoints, shipping a worktree, the Inbox and approvals, push notifications, pairing a phone, mail, other machines, clients, events, MCP, the tmux shim, herdr's command line, pane grants, configuration, agent features off, errors and recipes.

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。

Scan a codebase for missing, janky, or inconsistent UI motion and fix it with transitions.dev recipes. ALWAYS use this skill when the user's message is or contains a transitions-agent command (npx transitions-agent, npx transitions-agent fix, any variant) - the command is a request for the full guided flow, not just command execution. Also use when the user asks about UI transitions, animations, motion quality, a motion score, janky or missing transitions, "polish the motion", "fix the animations", or whether the motion is good after UI changes.

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。

Battle-tested Playwright patterns for E2E, API, component, visual, accessibility, and security testing. Covers locators, assertions, fixtures, network mocking, auth flows, debugging, and framework recipes for React, Next.js, Vue, and Angular. TypeScript and JavaScript.

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。

Battle-tested Playwright patterns for E2E, API, component, visual, accessibility, and security testing. Covers locators, fixtures, POM, network mocking, auth flows, debugging, CI/CD (GitHub Actions, GitLab, CircleCI, Azure, Jenkins), framework recipes (React, Next.js, Vue, Angular), and migration guides from Cypress/Selenium. TypeScript and JavaScript.

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。

给 AI 短剧出分镜：三层结构——段（一次视频生成，≤15 秒）→ 分镜（段内 2–5 秒的剪切，认领剧本节拍） → 分镜图（每切一张关键帧：主分镜图钉 0.00 秒，子分镜图钉各自切点）。 每段自带一条 MiniMax H3 视频提示词（官方口径默认英文、逐镜换行，promptLang 可切中文）：对齐指令和 [Shot k] 切点时刻由分镜结构推导、逐字对账，台词逐字进 <d> 块（写法规范已内化为 references/h3-prompt.md，不依赖外部 skill）。 产出 storyboard.json + Markdown + 单页评审报告（分镜节奏带 / 分集分镜表 / 生成批次单 / 配音对齐单，含导出 JSON）。不出图——交付的是每格的画面提示词和它该挂哪些参考图。 18 道质量门全部由脚本确定性检查（第 18 道 shot-recipe 可选：挂上 shot-recipes 卡库才查，不挂就明说跳过）； export 一键导出 H3 投产包（每段提示词 + 按 Picture 序的分镜图清单）。零依赖、零 API key，用当前会话额度。 Use when asked to 分镜、出分镜、镜头表、切镜、storyboard for AI short drama。

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。

Verify BB user journeys in an isolated source dev app using dev-browser@next and the matching source CLI. Use after BB feature changes or when asked to verify or smoke-test BB. The feature map covers core UI and agent interfaces, every repository plugin, desktop, mobile, and hosted services; select the affected recipes and platform prerequisites.

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 Megatron-LM (MLM) and Megatron Bridge training with mock or real data. Covers correlation testing, available recipes, and multi-GPU examples.

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。

Recommend and customize Megatron Bridge library and benchmark recipes for a user's model, GPU count, hardware, sequence length, and pretrain/SFT/PEFT goal. Use when selecting a starting recipe, comparing library and benchmark configs, resizing parallelism for a GPU allocation, or distinguishing convergence changes, semantics-preserving execution tuning, and benchmark-only shortcuts.

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。

Create and modify NeMo AutoModel training and evaluation recipes, including YAML structure, builders, and execution flow.

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。

Autonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger. Do NOT use for: bug fixes, code review, documentation, refactoring, dependency updates, or single-file changes.

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。

Playbook for launching, monitoring, stopping, and debugging NeMo-RL recipes on a Kubernetes cluster via the nrl-k8s CLI. Covers ephemeral vs long-lived RayCluster modes, iterating on runs, and debugging hung or failed training jobs.

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 and automates custom image builds with EC2 Image Builder - Linux, Windows, and macOS AMIs, and container images to ECR. Covers the build IAM role, Amazon-managed and custom components, image recipes, infrastructure and distribution configuration (launch templates, SSM parameters, other Regions), one-off builds, recurring scheduled pipelines for golden AMI automation and OS patching, custom image workflows, and diagnosing failed builds. Applies when creating, automating, or scheduling AMI or container image builds with Image Builder, or when debugging a failed build. Not for launching instances from existing AMIs, AMI lifecycle/retirement, or general EC2 fleet management.

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。

Turns one-shot external recon into a continuous monitoring program. Covers the scheduled re-scan-and-diff loop (baseline snapshot -> interval sleep -> re-scan -> asset/finding delta -> threshold-gated webhook alert), the scan-to-scan diff engine (new/removed/changed assets by a tracked-attribute table, new/resolved findings by a stable cross-scan fingerprint), adversary CTI / chatter monitoring across six public feeds (ransomwatch, ransomware.live, HackerNews Algolia search, Reddit security-subreddit RSS, GitHub Gist code-search, public Telegram channel scraping) with a source-kind-aware severity engine (leak-site/forum/telegram/paste tiers, CRITICAL through INFO), literal/glob/regex watchlist pattern matching, full-corpus capture with retroactive rescan on new watchlist entries, infrastructure-tracking-over-time discipline (certificate-transparency, passive-DNS, port/service, and typosquat re-enumeration cadence, and what a genuine 'perimeter drift' event looks like in the diff output), a five-state finding-lifecycle state machine (open/triaged/risk_accepted/resolved/false_positive) with per-severity SLA and fingerprint-based cross-scan dedup and auto-resolve/reopen rules, the alert-fatigue trap where a lifecycle-unaware rule re-fires on an already-accepted finding, a durable retry/backoff alert-outbox pattern ('queued is not delivered'), and copy-paste bash-cron plus PowerShell-Scheduled-Task recipes for a re-scan+diff loop with the Slack-compatible webhook payload shape. Passive OSINT and analysis only -- no new active-intrusion technique. Use when setting up ongoing monitoring for a retainer or MSSP engagement, tuning alert thresholds to avoid fatigue, triaging a finding's lifecycle status, investigating adversary chatter about a brand, building a 'what changed on the perimeter since last week' report, or deciding whether a persisting finding should re-alert.

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。

Rigorous, defensible email-spoofability verdict and SPF supply-chain risk analysis computed from published DNS alone. Deepens the record-level SPF/DMARC/DKIM/BIMI/MTA-STS/DNSSEC fetch recipes in the offensive-osint arsenal (§16.14) with the reasoning that section doesn't do: a priority-ordered composite verdict for whether an attacker can actually land header-From-spoofed mail in an inbox, and by which vector (exact-domain vs subdomain) — grounded in the single most-misunderstood distinction in email security: the envelope MAIL FROM that SPF authenticates vs the visible header From: that only DMARC governs. Explains precisely why SPF -all/~all alone is NOT spoof-proof without DMARC enforcement, and why SPF +all bypasses DMARC even under p=reject pct=100. Covers RFC 7208 §4.6.4's 10-DNS-lookup / 2-void-lookup PermError fail-open condition with a runnable stdlib-only lookup-counter script, plus the SPF-include-takeover supply-chain vector (an attacker re-registering a dead include inherits SPF-pass authority over the victim domain) with strict transient-vs-NXDOMAIN discrimination discipline so a temporary SERVFAIL is never mistaken for a takeover lead. Fully passive: DNS TXT reads only, no mail sent, no RCPT TO probe, no API keys. Use when auditing a domain's real spoofing resistance (not just its published records), explaining to a client why 'we have SPF -all' does not mean they're covered, investigating an SPF PermError or an unusually long include chain, evaluating a dead SPF include as a takeover lead, or writing a defensible spoofability finding for a deliverable.

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。

Convert Chinese stories or ordered local images into silent hand-drawn Remotion videos, with generated hand lettering, 327 built-in assets (297 style recipes and 30 theme palettes), a curated 30-style menu, and automatic reference-image style analysis with optional private reuse. Use when users ask to generate, import, restyle, preview or render hand-drawn story videos; browse or classify styles; imitate the visual grammar of a reference image; or save a reference-derived style. Preserve the approved colored-pencil diary default when no other style is requested.

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。

This skill should be used when picking or diagnosing a training move (SFT, LoRA, DPO/KTO/ORPO, RFT, GRPO/PPO/RLOO, RLHF), or when the user mentions fine-tuning, post-training, training recipe, reward design, or weight updates. Decision tree by reward shape, smoke-run gate, three failure diagnostics, five false-progress patterns. Provider recipes and I/O contract in references/.

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。

Two scopes: (1) drives Kimi.app via computer-use for Work/Agent data-plugin queries (天眼查、同花顺 iFinD、SEC、IMF etc.) and Chat's built-in 深度研究 report; (2) kimi-cu macOS desktop-automation playbook — AX set_value / keyboard / click channel selection, foregrounding, AX-tree recovery, form & dialog recipes. Use for "用 Kimi 查" / "操作 Kimi 客户端" / "Kimi 插件" / "Kimi 深度研究" / driving any macOS desktop app (Electron/webview/native) via kimi-cu. Not for kimi.com browser automation (use kimi-webbridge) or direct iFinD API access.

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 connecting to VidSeeds.ai, getting AUTH_REQUIRED or SUBSCRIPTION_REQUIRED from the vidseeds MCP server, or setting up VIDSEEDS_PAT / OAuth for the connector. Not for workflow recipes - use vidseeds-efficiency and domain skills after connect.

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。

Source authentic, high-res PUBLIC-DOMAIN artwork from museum open-access APIs (Met, Cleveland, SMK, Rijksmuseum, NGA, Art Institute of Chicago, Getty, Smithsonian) instead of AI-generated or generic-stock imagery. The default move whenever a visual needs an aesthetic, credible image (blog heroes, decks, social cards, essay/spec figures). Verified keyless recipes + licensing rules inside.

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。