“init”的搜索结果

Build container-based Foundry Agents with Azure AI Projects SDK (ImageBasedHostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.

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Provision database infrastructure, initialize migration framework, configure environments, and verify connectivity/migration gates

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TanStack Virtual headless virtualization for React. Use when rendering large lists (100+ items), implementing virtual scroll, building infinite scroll feeds, virtualizing grids or tables, using window-level scrolling, or implementing masonry/lane layouts with @tanstack/react-virtual. Triggers on: useVirtualizer, useWindowVirtualizer, virtual list, virtual scroll, list virtualization.

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Bu Flutter template'inde uctan uca yeni feature iskelesi kurar — lib/feature/<ad>/ klasor yapisi, Freezed state + Cubit, StatelessWidget ya da StatefulWidget+ViewModel view, BlocProvider yerlesimi (global state_initialize mi lokal mi), TypedGoRoute, LocaleKeys cevirileri, AppPaddings/textTheme/colorScheme token'lari ve zorunlu <feature>.md modul dokumani. Kullanici "yeni feature ekleyelim", "su sayfayi projeye gore yaz", "cubit + state + view kur", "feature iskeleti cikar", "scaffold a feature" dediginde kullan.

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Use when working with Cucumber — cucumber BDD testing management and analysis. Covers feature file organization, step definition mapping, scenario tagging, Gherkin syntax validation, test report parsing, and step reuse analysis. Use when managing Cucumber test suites, investigating BDD scenario failures, or reviewing feature file coverage.

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Use when working with Crossplane — crossplane Kubernetes-native infrastructure management. Covers managed resources, compositions, provider configurations, composite resource definitions (XRDs), claims, and provider health. Use when managing Crossplane resources, debugging provisioning failures, inspecting compositions, or auditing cloud resource status.

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Use when working with Aws Fargate — aWS Fargate task and service analysis covering ECS cluster inventory, Fargate task status, CPU and memory utilization, task definition review, networking configuration, service auto-scaling policies, and container health checks. Use for Fargate-specific workload optimization.

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Use when working with Azure Logic Apps — azure Logic Apps workflow run analysis, trigger history, connector management, error diagnostics, and workflow definition inspection via Azure CLI.

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Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.

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API + Python SDK for ordering cell-free protein expression and binding assays. Submit sequences for expression (10–100 µg), measure binding affinity (KD) against targets, track status, and retrieve results programmatically — no wet-lab setup. Built for ML-guided directed evolution and antibody/nanobody optimization. Requires Adaptyv account and API key.

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Start a new composition: project init, brainstorm, then ask whether graph or startcycle follows. Generated from plugin-commands.json; invoke as $bdb-aos:startproject.

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Initialize, update, and visualize codebase or personal knowledge wikis using LangChain OpenWiki. Enforces OKF v0.2, Grounded Claims, interactive visualizer graph, and MCP page-job lifecycle.

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Interview a project folder into AOS and write the result: a stable slug and domain in .aos/project.json, an OpenWiki wiki that is actually watched and does not index junk, memB memory bound to the slug, a Synapse map, AGENTS.md with its harness symlinks, and optionally CI and issue triage.

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既存プロジェクトの初期セットアップ（初回のみ）。コードリポジトリを分析してCLAUDE.md、要件概要、 基本設計書（アーキテクチャ、DB設計、API設計）、OpenAPI仕様、MkDocs設定を自動生成する。 「このプロジェクトをセットアップして」「既存コードを分析して」「設計書を初期化して」 「プロジェクトの構造を把握して」などのリクエストで使用する。 既にドキュメントがある場合は移行モードで差分だけ補完する。 ※ 既存Specの全更新・再生成には spec-all を使う。

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iOS design system tokens for Pencil MCP: SF Pro typography scale, iOS semantic colors (light + dark mode hex values), spacing grid, touch targets, corner radii, and component heights. Use when initializing a .pen file for iOS design or setting up design variables.

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Implement Swift Codable models for JSON and property-list encoding and decoding with JSONDecoder, JSONEncoder, CodingKeys, and custom init(from:) or encode(to:). Use when parsing API responses, remapping keys, flattening nested JSON, handling date or data decoding strategies, decoding heterogeneous arrays, or integrating Codable with URLSession, SwiftData, or UserDefaults.

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Refactor and review SwiftUI view files with strong defaults for small dedicated subviews, MV-over-MVVM data flow, stable view trees, explicit dependency injection, and correct Observation usage. Use when cleaning up a SwiftUI view, splitting long bodies, removing inline actions or side effects, reducing computed `some View` helpers, or standardizing `@Observable` and view model initialization patterns.

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Autonomous build-verify-fix loop that runs until an explicit Definition of Done passes. Use when named (mini-loop) or when the user says exactly "run a loop".

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Project code patterns and conventions. Auto-loads when implementing, designing, verifying, or reviewing code. Provides detailed pattern definitions with code examples.

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Design and generate Convex database schemas with proper validation, indexes, and relationships. Use when creating schema.ts or modifying table definitions.

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Use when: planner mode, planning mode, proposal, scope definition, estimate, timeline, how hard, feasibility, effort, how long, how big, client message, external communication, pricing, delivery confidence, commercial risk, or project delivery planning.

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This skill should be used when the user asks to "identify web application vulnerabilities", "explain common security flaws", "understand vulnerability categories", "learn about injection attacks", "review access control weaknesses", "analyze API security issues", "assess security misconfigurations", "understand client-side vulnerabilities", "examine mobile and IoT security flaws", or "reference the OWASP-aligned vulnerability taxonomy". Use this skill to provide comprehensive vulnerability definitions, root causes, impacts, and mitigation strategies across all major web security categories.

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Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.

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Build container-based Foundry Agents with Azure AI Projects SDK (ImageBasedHostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.

中文简介正在准备中。当前显示原文说明。