“sandboxes”的搜索结果

Test payment and checkout flows end to end against PSP sandboxes — Stripe first, with the general pattern for Adyen/Braintree/PayPal. Covers Stripe test-mode card numbers and their decline codes, the 3DS/SCA challenge flow and its nested-iframe handling in Playwright, test clocks for subscription/billing-cycle simulation, webhook testing (stripe listen/trigger, signature verification, idempotency), failed/retried payments and refunds, and never using real cards. Use when: "test Stripe checkout," "payment test," "3DS test," "test webhook signature," "test subscription renewal," "test clock," "refund test," "decline card test," "checkout E2E." Not for: General API contract testing of non-payment endpoints — api-testing. PCI-DSS/regulatory compliance audit — compliance-testing. Related: api-testing, playwright-automation, compliance-testing, test-data-management, qa-project-context.

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E2B is a cloud platform that gives AI agents secure, isolated sandboxes — ephemeral Linux VMs with a filesystem, package managers, and internet access — to run AI-generated code safely. Use when a user wants an agent to execute Python or JavaScript, install packages, read/write files, or run a long process without risking the host machine, or wants to wire code execution into a LangChain, CrewAI, or custom agent loop.

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Run AI agent code safely in isolated sandboxes with resource limits, audit trails, and kill switches. Use when someone asks to "sandbox my agent", "run agent code safely", "add guardrails to AI agent", "isolate agent execution", "audit agent actions", "prevent agent from deleting files", "restrict agent permissions", or "add safety controls to AI coding agent". Covers Docker isolation, filesystem restrictions, network policies, resource locking, and comprehensive audit logging.

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Configure or diagnose file and directory access, mounts, and host ACLs for AWF sandboxes.

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Designs approval and sandbox policy for local coding agents: permission modes, isolation, network and destructive-command guards. Use when setting approvals. Not cloud sandboxes.

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Expert guide for ephemeral WebAssembly (WASM) and isolated micro-runtime sandboxes to securely execute AI-generated code, validate database migrations in-memory, and perform sub-millisecond fuzzing / Panduan ahli sandbox WebAssembly (WASM) efemeral dan micro-runtime terisolasi untuk eksekusi kode AI yang aman, validasi migrasi database in-memory, dan fuzzing sub-milidetik.

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Stop the background HTTP registry server started by /start-http-registry — TaskStop / KillShell by the recorded task ID, plus a /proc cmdline-scan fallback for minimal-tool sandboxes with no ps/lsof/pkill/fuser. Referenced by every warp deploy/update skill that starts the registry.

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Cloudflare platform management via Wrangler CLI, Agents SDK (v0.13+), and Browser Rendering API. Deploy Pages, Workers, KV, R2, D1, Queues, Vectorize, Workflows, Hyperdrive. Build stateful AI agents with the full SDK stack — Agent, AIChatAgent, Think, Voice, sub-agents, fibers, HITL, scheduling, observability, Code Mode (Dynamic Worker sandboxes). Budget web scraping via cf_browser.py. Use when deploying to Cloudflare, managing CF infrastructure, configuring wrangler.toml/wrangler.jsonc, building AI agents or chat agents on Workers, adding voice, orchestrating sub-agents, or for cheap web scraping. Triggers: Cloudflare, wrangler, Pages, KV, R2, D1, Workers, Vectorize, Queues, Workflows, Hyperdrive, cf_browser, Browser Rendering, Agents SDK, Code Mode, codemode, MCP, Think, AIChatAgent, Voice agent, sub-agents, fibers, HITL, Dynamic Workers.

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Cloudflare-first platform selection. Decision trees for Workers, D1, R2, KV, DO, Queues, Vectorize, Containers, Sandboxes, Flagship, Agent Memory, Workflows v2. Default stack, override conditions, auth, data patterns, reliability.

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Identify and exploit Server-Side Template Injection (SSTI) vulnerabilities within web applications. Use this skill when testing web applications that render dynamic content using template engines like Jinja2 (Python), Twig (PHP), Freemarker (Java), or Pug (Node.js). Covers identification via mathematical evaluation, context mapping, escaping sandboxes, and achieving Remote Code Execution (RCE).

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三大闭环日常健检（v2.0）。快速读取系统状态文件（约1分钟），从三个层次输出健康仪表盘：①运营指标层（PENDING-EXPERIENCES/碎片积压/一致性检查日期/cascade/PENDING-SKILLS）②沙盘状态层（sandboxes/目录的 validated/draft/gap-found 分布）③D0覆盖率层（role-* Skills 有多少已有认知根行）。触发词：「三大闭环健康检查」「全系统健康报告」「整体系统健康」「三个闭环都健康吗」「三大闭环状态怎么样」。⚠️ 本 Skill 为快速只读健检，无 Full 模式。深度场景沙盘验证→skill-closure-verifier-meta；生成场景沙盘→scenario-sandbox-builder；单一Loop专项→对应专项Skill。

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Orchestrate AI coding agents (Claude Code, Codex, OpenCode) in isolated sandboxes using the @ai-hero/sandcastle SDK. Use when the user needs to (1) run agents AFK in Docker/Podman containers, (2) build multi-agent pipelines with plan-execute-review patterns, (3) run parallel agents on separate worktrees, (4) create iterative agent loops with maxIterations, (5) extract structured output from agent runs, (6) set up sandcastle in a new or existing project, or (7) write prompt files with template args and shell expressions.

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Use when designing or reviewing Salesforce sandbox topology, refresh cadence, masking, and environment purpose. Triggers: 'Developer sandbox', 'Developer Pro', 'Partial Copy', 'Full sandbox', 'sandbox refresh', 'data masking', 'test environment', 'Gov Cloud sandbox'. NOT for how many environments a program needs and how they map to branches - use devops/environment-strategy. NOT for re-seeding reference data after a refresh - use data/sandbox-refresh-data-strategies. Also covers: SandboxPostCopy Apex class, SandboxInfo and SandboxProcess Tooling API, SandboxSettings metadata, sandbox topology table, refresh calendar.

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Generalize published Spectre and remote microarchitectural research into passive target prerequisites, defensive review, and approval-gated local validation. Use for shared runtimes, JavaScript isolates, edge workers, serverless platforms, browser sandboxes, remote timing, cache side channels, speculative type confusion, or Dynamic Process Isolation analysis.

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E2B Desktop Sandbox with autonomous computer use — cloud Linux environments for browser automation, visual UI grounding, screenshot analysis, and shell execution. Supports Browser Use cloud sessions, Playwright integration, and LLM-driven desktop control. Use when asked about sandboxes, computer use, browser automation, E2B, desktop control, visual testing, or cloud Linux environments.

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Run Cua sandboxes locally - no API key required. Covers Docker (XFCE/Kasm) for Linux containers, QEMU for full VMs, Lume for macOS guests on Apple Silicon, and Tart for Apple VZ VMs. Use when the user wants a local sandbox, wants to keep things off the cloud, or asks "spin up an Ubuntu desktop", "open a sandbox VM", "let me try this safely first".

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pi-cua-integration is a Pi/Senpi extension that bridges Cua (trycua/cua) for computer-use sandboxes and host control. MUST USE when the user asks to drive a desktop UI, take screenshots, run a "computer use" task, control a sandbox, or invoke any cua_* tool. Triggers - "cua", "computer use", "sandbox", "screenshot the desktop", "click the screen", "take over the browser", "샌드박스 켜줘", "스크린샷 찍어", "내 컴퓨터에서 자동화".

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Cloudflare-first platform selection. Decision trees for Workers, D1, R2, KV, DO, Queues, Vectorize, Containers, Sandboxes, Flagship, Agent Memory, Workflows v2. Default stack, override conditions, auth, data patterns, reliability.

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Claude Managed Agents (platform.claude.com) リファレンス。Agents / Sessions / Environments API, SSE event streaming, event deltas, session threads, session budgets, multiagent orchestration (subagents, dynamic workflows, workflow runs, advisor), deployments (cron), dreams, vaults, memory stores, self-hosted sandboxes, webhooks, web search / fetch ドメイン制限, secure deployment, permission policies, Agent Skills, MCP connector, user profiles。

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Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus

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Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges

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Use when you need to visually interact with a GUI — test buttons, fill forms, verify visual layouts, fuzz web pages, automate user flows, take screenshots, or perform end-to-end QA on any application. Works on cloud VMs, Docker containers, local machines, and sandboxes. Install: pip install cua.

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Design RL simulation sandboxes, trajectory datasets, QLoRA/LoRA adaptation plans, eval harnesses, and rollback unhooks for agents learning specific coding behaviors beyond the base model. Use when building or reviewing tool-use training loops, offline trajectories, reward functions, self-improvement harnesses, or Port Daddy agent behavior curricula. NOT for generic ML tutorials, full model training operations, or production deployment without eval gates and safety unhooks.

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Runs Docker Desktop and its WSL2 layer, checking RAM and disk before container work. Trigger when Docker Desktop or a container won't start, vmmem eats RAM or the Docker disk keeps growing; to set a WSL memory cap in .wslconfig; to list or install WSL distros; to bring a compose stack up or down; to prune images and build cache; to run a command in a container; to log in to a registry; or say dockerrunner (audit, check, up, down, prune, status, refresh). Local LLMs (Docker Model Runner too) are lmstudiorunner's; images comfyrunner's; VMs and sandboxes hypervrunner's; Docker's MCP catalog its MCP Toolkit's; registry tokens keywarden's.

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