「onboard」の検索結果

Draws original hand-written SVG spot scenes in the Line interior style, wide airy rooms or terraces where slim, realistic people do design and coding work. A thin uniform indigo outline (1.4 px at 480 wide) runs around mostly white fills. Sparse flat accents (teal, sage, coral, mustard, lavender, peach wood) cover under 7% of the card. Pale lavender 1 px background decor (brick clusters, pendant lamps, framed posters) sits behind, and a long floor line with end dashes runs under it all. Covers the palette, line weights, heads and hands from a parts toolkit, composition and a render-critique loop. Use when asked for line-art, thin-line or outline illustrations, indigo line art, office, desk, home-workspace, remote-work or team scenes, or interior spot illustrations for empty states, onboarding screens, 404 pages, blog headers, feature spots, landing sections or marketing cards.

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 Solana applications with Helius infrastructure. Covers transaction sending (Sender), asset/NFT queries (DAS API), real-time streaming (WebSockets, Laserstream), event pipelines (webhooks), priority fees, wallet analysis, and agent onboarding.

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 a production 1:1 stablecoin swap with LI.FI Intents — an interface or backend where the amount the user sends equals the amount they receive (no visible gas or solver fees), same-chain or cross-chain, filled by LI.FI's solver network and verifiable on-chain. USE THIS SKILL WHEN USER WANTS TO: - Build a 1:1 stablecoin swap interface ("send 100 USDC, receive 100 USDC"), same- or cross-chain - Add stablecoin transfers with a guaranteed output amount to an app, backend, or bot - Build enterprise/fintech-grade transfers with no visible gas or solver fees for the end user - Implement the LI.FI Intents quote -> approve -> escrow open -> status loop for stablecoins - Move USDC / USDT 1:1 across chains under an onboarded LI.FI integrator - Understand how the LI.FI integrator ID / Partner Portal enables 1:1 quoting - Use the @lifi/intent TypeScript SDK to quote, build, open, and track an intent order This skill is self-contained and covers the integration end to end via the `@lifi/intent` SDK (the primary path), with the raw `order.li.fi` REST endpoints as a language-agnostic option. For the wider LI.FI product surface (classic swaps/bridges, Composer, Earn), use the `lifi` skill.

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。

Guided onboarding wizard for Ouroboros setup

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。

Start Ouroboros onboarding. Use when the user sends bare `ooo`, asks to start Ouroboros, or is using Ouroboros for the first time.

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 custom subagent definitions for Claude Code (.claude/agents/*.md) and Codex (.codex/agents/*.toml): loadability against the native schema, description overlap, model tier, tool scope, and headless-safe instructions. Use when onboarding to a project with agents, after adding or importing agents, or when the parent agent delegates to the wrong agent.

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 or revise software documentation using the Diátaxis distinction between tutorials, how-to guides, reference, and explanation. Use for README sections, product and API documentation, operational guides, onboarding material, or restructuring an existing documentation set.

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。

Friendly onboarding when users ask about capabilities

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。

Analyze brownfield codebase and create initial continuity ledger

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。

Google Ads account audit and business context setup. Use for account-health audits and business-context setup. Trigger on "audit my ads", "ads audit", "set up my ads", "onboard", "account overview", "how's my account", "ads health check", "what should I fix in my ads", or when the user is new to NotFair and hasn't run an audit before.

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。

Meta Ads (Facebook + Instagram) account audit and business context setup. Use for account-health audits and business-context setup. Trigger on "audit my Meta ads", "audit my Facebook ads", "Meta ads audit", "set up my Meta ads", "onboard Meta", "Meta account overview", "how's my Meta account", "Meta health check", "what should I fix in my Facebook ads", or when the user is new to NotFair Meta and hasn't run an audit before.

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 the developer experience of a product, SDK, docs site, or SKILL.md by dropping multiple Claude subagents at it with only a tiny task prompt and real tools (WebFetch, Bash, Write). Agents must discover the docs themselves, install deps, ask for credentials if needed, and attempt real execution. The skill captures each agent's trace — tool calls, retries, wall time, errors — and scores on Setup Friction, Speed, Efficiency, Error Recovery, and Doc Quality, then emits an HTML report with an A–F grade and concrete fixes. Use when the user asks to audit agent experience, test a skill, audit docs for agents, check if a SDK is agent-friendly, validate a SKILL.md, measure agent DX, or benchmark how painful onboarding is for an AI agent. Triggers: 'audit agent experience', 'test this skill', 'audit docs for agents', 'is my SDK agent-friendly', 'run a DX audit', 'agent experience test', 'test my docs', 'how do agents do with my product'.

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 a comprehensive project summary from milestone artifacts for team onboarding and 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。

Set up CIAgent regression testing for the AI agent in this repo — write a runner, record golden baselines, generate a test spec, and verify it. Use when the user asks to add tests, evals, or regression testing for their AI agent, or to set up CIAgent.

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。

管理账号画像全生命周期：创建空白画像、编辑六维字段、更新记忆、切换、导出和对比。 当用户说“新建/编辑/更新/切换/导出/对比画像、写进画像记忆”时使用。 首次从社媒数据生成画像用 skill-profile-builder；只提炼语言风格用 skill-voice-builder；品牌首次入驻引导用 skill-brand-onboarding。

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 a user needs to get started with PAIDF Auto-Labeling, plan a scenario, run or debug a shipped cookbook, author prompts or cookbooks, migrate a pipeline, or configure a stage. Confirm critical inputs (data path, output path, endpoints) and ask when any are missing. This is a router: read the matching reference instead of inventing a 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。

Orient users to the i4h workflow runtime and route them to the correct stage skill. Use for architecture, support, or where-to-start questions; do not execute a known stage.

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 for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance.

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。

Explains this repository's shared Claude Code setup to a new teammate, covering what is committed and shared, what stays personal, and what the team-kit plugin adds. Use when someone asks how the team's Claude Code setup works or what they get by cloning the 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。

Analyzes code repositories and generates hierarchical documentation structures with onboarding guides. Use when the user wants to create a wiki, generate documentation, map a codebase structure, or understand a project's architecture at a high level.

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。

Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".

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。

Assess whether source code is ready to deploy to Azure — the check BEFORE infrastructure work. Evaluates build health, app completeness, dependencies and local services, stack compatibility, and deployment feasibility. Answers questions about what your app needs before it can be deployed — frameworks, dependencies, and configuration. Checks whether dependencies are compatible and identifies deployment blockers and unsupported frameworks. WHEN: "evaluate my repo", "is my app ready to deploy", "what does my app need to deploy", "what do I need before deploying", "does my app need", "can I ship this to Azure", "scan my repo for issues", "is this app deployable", "check if my app is ready for Azure", "do I need a Dockerfile", "what's blocking my deployment", "are there any blockers", "are my dependencies compatible", "does Azure support my framework", "what needs to change before deploying", "check my app configuration".

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, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).

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。

Design the first-run experience — activation path, progressive disclosure, and time to first value. Use for a user's very first session. For the mechanics of the signup form itself, use `form-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。