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skyvern

Automate any website with AI-powered browser automation. Use when the user needs to interact with a website like filling forms, extracting data, downloading files, logging in, or running multi-step workflows. Skyvern navigates sites it has never seen before using LLMs and computer vision. Integrates via Python SDK, TypeScript SDK, REST API, MCP server, or CLI.

DeepseekModel キュレーション済みスキル 品質 優秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=skyvern-ai-skyvern-docs-skill-md&format=skill
ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
name skyvern description Automate any website with AI-powered browser automation. Use when the user needs to interact with a website like filling forms, extracting data, downloading files, logging in, or running multi-step workflows. Skyvern navigates sites it has never seen before using LLMs and computer vision. Integrates via Python SDK, TypeScript SDK, REST API, MCP server, or CLI. license AGPL-3.0 compatibility Requires a Skyvern Cloud API key (https://app.skyvern.com) or a self-hosted Skyvern instance. Python SDK requires Python 3.11+. TypeScript SDK requires Node.js 18+. MCP server works with Claude Code, Claude Desktop, Cursor, Windsurf, and VS Code. metadata {"author":"skyvern-docs","version":"1.0","docs":"https://skyvern.com/docs","github":"https://github.com/Skyvern-AI/skyvern"} Skyvern: AI Browser Automation Skyvern automates browser-based workflows using LLMs and computer vision. It navigates websites it has never seen before, filling forms, extracting data, and completing multi-step tasks via a simple API. SDK reference (all methods, parameters, types in one page): https://skyvern.com/docs/sdk-reference/complete-reference When to use Skyvern The user needs to interact with a website programmatically (fill forms, click buttons, navigate pages) The user needs to extract structured data from a website (scrape prices, addresses, table rows) The user needs to download files from a web portal (invoices, reports, statements) The user needs to log in to a website and perform actions behind authentication The user needs to automate a multi-step workflow across one or more websites The user needs to run browser automation from an AI assistant (Claude, Cursor, Windsurf) Capabilities Run a single task Execute a one-shot browser automation with natural language instructions. Inputs: prompt (required): Natural language description of what to do url (required): Starting page URL data_extraction_schema (optional): JSON schema for structured output proxy_location (optional): Country code for geo-routing (e.g., US , DE ) Python SDK: from skyvern import Skyvern client = Skyvern(api_key= "YOUR_API_KEY" ) result = await client.run_task( prompt= "Get the title of the top post on Hacker News" , url= "https://news.ycombinator.com" , ) TypeScript SDK: import Skyvern from "@skyvern/client" ; const client = new Skyvern ({ apiKey : "YOUR_API_KEY" }); const result = await client. runTask ({ prompt : "Get the title of the top post on Hacker News" , url : "https://news.ycombinator.com" , }); REST API: curl -X POST https://api.skyvern.com/api/v2/run \ -H "x-api-key: YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{"prompt": "Get the top post title", "url": "https://news.ycombinator.com"}' Extract structured data Define a JSON schema to get consistent, typed output from any page. result = await client.run_task( prompt= "Extract the top 3 posts" , url= "https://news.ycombinator.com" , data_extraction_schema={ "type" : "object" , "properties" : { "posts" : { "type" : "array" , "items" : { "type" : "object" , "properties" : { "title" : { "type" : "string" }, "url" : { "type" : "string" }, "points" : { "type" : "integer" } } } } } }, ) Build multi-step workflows Chain task blocks, loops, conditionals, data extraction, and file operations into reusable automations. Block types: NavigationBlock, ActionBlock, ExtractBlock, LoopBlock, TextPromptBlock, LoginBlock, FileDownloadBlock, FileParseBlock, UploadBlock, EmailBlock, WebhookBlock, ValidationBlock, WaitBlock, CodeBlock, ForLoopBlock, WhileLoopBlock, FileURLParsingBlock, DownloadToS3Block, SendEmailBlock. Use a ForLoopBlock when the workflow already has a fixed list to iterate over, such as extracted rows, uploaded files, or user-provided URLs. Use a WhileLoopBlock when the workflow should keep repeating until a condition changes, such as paginating while a Next button remains enabled, polling until a status is complete, or retrying while a recoverable page state is visible. workflow = await client.create_workflow( title= "Invoice Downloader" , blocks=[...], # See workflow blocks reference ) run = await client.run_workflow(workflow_id=workflow.workflow_id) Manage browser sessions Persist a live browser across multiple tasks to maintain login state, cookies, and page context. session = await client.create_session() # Run multiple tasks on the same browser await client.run_task(prompt= "Log in" , url= "https://example.com" , browser_session_id=session.browser_session_id) await client.run_task(prompt= "Download invoice" , url= "https://example.com/billing" , browser_session_id=session.browser_session_id) await client.close_session(session.browser_session_id) Handle authentication Store passwords, TOTP/2FA secrets, and credit cards securely. Skyvern auto-fills login forms and generates 2FA codes during automation. Supported credential providers: Skyvern vault (built-in), Bitwarden, 1Password, Azure Key Vault. Use via MCP server Connect AI assistants directly to browser automation. The MCP server exposes 75+ tools. Install for Claude Code: claude mcp add skyvern-cloud -- npx @anthropic-ai/skyvern-mcp@latest --skyvern-api-key YOUR_API_KEY Install for Cursor/VS Code: Add to MCP config: { "mcpServers" : { "skyvern" : { "command" : "npx" , "args" : [ "@anthropic-ai/skyvern-mcp@latest" , "--skyvern-api-key" , "YOUR_API_KEY" ] } } } Use via CLI pip install skyvern export SKYVERN_API_KEY= "YOUR_KEY" skyvern browser session create # Start a cloud browser skyvern browser act "Click the login button" # Natural language action skyvern browser extract '{"title": "string"}' # Extract structured data skyvern browser screenshot # Capture screenshot skyvern task run --prompt "..." --url "..." # Run a task skyvern workflow run -- id wf_xxx # Run a workflow Constraints Tasks run in cloud browsers managed by Skyvern (or self-hosted browsers). They do not run in the user's local browser by default. Each task step consumes credits. Set max_steps to control costs. Browser automation takes 30-120 seconds per task depending on complexity. Skyvern works best with natural language prompts that describe the goal, not low-level click instructions. For websites that require login, credentials must be stored via the credentials API before running tasks. Self-hosted deployments require Docker and a PostgreSQL database. Key references Quickstart : First task in 5 minutes SDK Reference : All methods and types (Python + TypeScript) MCP Server Setup : Connect AI assistants Workflow Blocks Reference : All block types Task Parameters : All task options Full documentation index : Complete page directory
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ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
同じスキルを各プラットフォーム形式で出力できます。
.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

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