'dev server' 검색 결과

LiteLLM proxy server setup, TypeScript client patterns via OpenAI SDK, model routing, fallbacks, load balancing, spend tracking, virtual keys, and production deployment

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Serverless GPU compute platform for AI model deployment — web endpoints, GPU functions, model serving, and TypeScript client patterns

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Full instrumentation from day one. PostHog consolidates product analytics + feature flags + error tracking (one platform, one bill). GA4 via GTM (14-step automation, custom dimensions over events, server-side tagging). Sentry (deep error tracking + performance). Stripe (webhook-first with idempotent processing). Listmonk on Coolify (newsletters via Amazon SES SMTP relay). PLG 7-layer framework. Programmatic SEO (5 page types). Incident auto-remediation via Sentry→Inngest pipeline. AI search (GEO) awareness. Local business conversions (phone_click, direction_click, form_submit, booking_click) with CRO patterns for both SaaS and local.

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Exploit Server-Side Request Forgery (SSRF) vulnerabilities in applications hosted on AWS to access the highly sensitive Instance Metadata Service (IMDS). This allows an attacker to steal valid IAM roles and temporary security credentials, leading to catastrophic cloud account compromise.

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DOM-based XSS occurs when JavaScript reads attacker-controlled sources (`location.hash`, `document.referrer`, `window.name`, `location.search`) and passes them to dangerous sinks (`document.write`, `innerHTML`, `eval`, `location.href`, `setTimeout`, `jQuery.html()`) without sanitization. Unlike reflected/stored XSS, payloads never reach the server. Detect by auditing JavaScript for tainted data flow from DOM sources to sinks. Tools: Burp Suite DOM Invader, Chrome DevTools, DOMPurify (fix).

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Exploit Server-Side Request Forgery (SSRF) vulnerabilities on Amazon Web Services (AWS) EC2 instances to access the highly sensitive Instance Metadata Service (IMDS). Circumvent basic protections and extract temporary IAM access keys, escalating privileges comprehensively across the AWS Cloud environment.

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Exploit misconfigurations in AWS Cognito, specifically focusing on unauthorized identity pool access, user pool self-registration issues, and privilege escalation via custom attributes to access broader AWS infrastructure.

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Exploit Server-Side Request Forgery (SSRF) vulnerabilities to extract AWS IAM credentials from the Instance Metadata Service version 2 (IMDSv2). This skill details how to bypass the token requirement of IMDSv2 by chaining HTTP verbs (PUT then GET) if the SSRF vulnerability allows full control over the request headers and methods.

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Exploit Server-Side Request Forgery (SSRF) vulnerabilities in applications hosted on AWS EC2 instances to extract IAM credentials and User Data from the Instance Metadata Service (IMDS). This skill covers techniques for bypassing basic filters to access IMDSv1 and concepts of IMDSv2.

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This skill provides expert-level guidance for VS Code extension development. Use when implementing new extension features, debugging extension code, designing WebView UIs, implementing Language Server Protocol features, or optimizing extension performance. Covers activation events, contribution points, VS Code API patterns, security best practices, testing strategies, and publishing workflows.

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Tracks adversary C2 and staging infrastructure by clustering indicators on shared attributes (TLS/JARM, certificate fields, favicon hashes, ASN, registration patterns) to find related hosts. Activates for requests to track adversary infrastructure, cluster C2 servers, or pivot on infrastructure attributes to find related hosts.

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Deploy and manage serverless applications on Volcengine veFaaS. Use when the user wants to deploy web apps, manage functions (pull code, upload and deploy), configure environment variables, inspect veFaaS projects, troubleshoot vefaas CLI/auth/framework issues, or work with veFaaS services.

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Deploy a local project directory or Git repository to Volcengine as a running, reachable cloud service. USE WHEN: deploy to Volcengine, deploy to 火山引擎/火山, deploy this repo/project, publish current code, launch the app, run it in the cloud, expose it as a service, deploy to ECS/VKE/veFaaS, run on ECS, push to VKE, deploy as serverless/FaaS, or the user wants the agent to choose a Volcengine hosting target. If the user only asks which Volcengine deployment target to choose, use `volcengine-prepare` skill first. Not for creating a single standalone resource — use `volcengine-cli` skill for that.

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Production-grade TypeScript reference for React & Next.js frontend development. Covers type narrowing, component Props, generic hooks, discriminated unions, as const, satisfies, Zod validation, TanStack Query, server/client boundaries, forms, state management, performance, accessibility, debugging, and code review. Use when the user works with TypeScript in React or Next.js: type errors, Props design, generics, API typing, SSR/CSR boundaries, hydration issues, form validation, state management, performance, or code review. Also use for "how should I type this?", "why does this type error happen?", or any architectural decision involving TypeScript in a frontend context.

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用于创建、配置、审查或调试基于 Vite 的前端项目、vite.config.ts、环境变量、dev server proxy、HMR、插件顺序、library mode、依赖预打包、bundle splitting 或 Vite 构建性能。React/Vue 组件架构请使用框架专项 skill；中文触发词包括 Vite 配置、vite.config、Vite 构建、Vite 性能。

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Use when creating, configuring, reviewing, or debugging Vite-based frontend projects, vite.config.ts, env variables, dev server proxy, HMR, plugin ordering, library mode, dependency pre-bundling, bundle splitting, or Vite build performance. Use framework-specific skills for React/Vue component architecture; Chinese triggers include Vite configuration, vite.config, Vite build, Vite performance.

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Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.

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Guides developers through downloading, configuring, and installing the official open-source Google Ads MCP Server. Use this skill when a user wants to connect their AI assistant (such as Gemini, Claude Code, or Cursor) to their Google Ads account to query campaigns or retrieve reporting metrics using natural language.

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Discovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.

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Stores, retrieves, and manages data as objects in Cloud Storage (Google Cloud Storage, or GCS) buckets. Use when you need to interact with Cloud Storage — create or configure buckets, upload, download, stream, or transfer data, organize objects with folders, generate signed URLs, control access (IAM, ACLs, public access prevention), set storage classes and tiering (Standard, Nearline, Coldline, Archive), manage cost and lifecycle, protect data (versioning, encryption/CMEK, retention and Bucket Lock, object holds, soft delete), host static websites, trigger Pub/Sub notifications on object changes, mount buckets as a file system (gcsfuse), or optimize storage performance at any scale. Covers the gcloud storage / gsutil CLI, JSON and XML APIs, client libraries, Terraform, and Cloud Storage MCP servers. Don't use for block storage (Persistent Disk), data warehousing/analytics (BigQuery), or databases (Cloud SQL, Spanner, Bigtable, Firestore).

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Diagnoses and resolves Google Cloud Filestore client mount failures, permission errors (EACCES), and network timeouts (ETIMEDOUT). Use when an NFS mount hangs or fails from a Compute Engine VM, GKE pod, Cloud Run service, or Vertex AI workload, when `mount.nfs` reports "Connection timed out" or "access denied by server", when checking whether VPC ingress firewall rules or `nfsExportOptions` allow a client IP, or when a previously working Filestore share suddenly stops mounting after an administrative change. Don't use for Cloud Storage (GCS) buckets, Persistent Disk, or Cloud NetApp Volumes, and don't use for Filestore capacity scaling or backup and export-policy auditing.

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Inspect Caveman Cloud's eval-gated experiment lifecycle and block unsafe execution. Use when the user asks to start, approve, cancel, promote, or roll back a Caveman experiment, or asks what action an experiment's evidence supports. Read evidence first; do not execute lifecycle mutations until server-authoritative transition and evidence gates ship.

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Interactive Claude Code environment setup wizard. Detects existing configuration, guides through best-practice setup for Global CLAUDE.md, project scaffolding, MCP servers, hooks, custom agents, keybindings, and settings. Use when user runs /devtools:code-env-setup, mentions "setup claude code", "configure claude", "claude code setup", "environment setup", or "initialize claude code".

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Setup Ubuntu server Nginx fail2ban backup monitoring disaster recovery — sysadmin ครบมือ

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