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HyperClockUp

DrissionPageMCPServer_Modified

by HyperClockUp

take_screenshot

Capture browser screenshots to visually confirm page elements before operations, provide visual context for AI analysis, and assist in debugging web automation tasks.

Instructions

截取页面截图(标准化工作流程第1步)

        ⚠️ 核心预处理工具:这是标准化工作流程的第1步!
        
        🎯 主要用途:
        1. 🔍 视觉确认:在任何元素操作前,先确认目标元素存在
        2. 📋 为多模态LLM提供视觉上下文信息
        3. 🐛 调试辅助:操作失败时用于问题诊断
        4. 📝 文档记录:保存操作过程的视觉证据
        
        💡 与其他工具的配合:
        - 多模态LLM:截图 → 视觉分析 → 精确操作
        - 非多模态LLM:截图 → get_page_text() → get_dom_tree() → 操作
        
        Args:
            filename: 截图文件名(可选,自动生成时间戳命名)
            full_page: 是否截取完整页面(True)还是可视区域(False)
            element_selector: 仅截取特定元素(可选)
            
        Returns:
            str: 截图保存路径和操作结果
            
        🚀 推荐使用场景:
        - 每次页面导航后立即截图确认加载状态
        - 点击、输入等操作前截图确认目标元素
        - 操作失败时截图辅助问题诊断
        

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameNo
full_pageNo
element_selectorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by explaining the tool's role in workflows, debugging assistance, and documentation purposes. It mentions '操作结果' (operation results) but doesn't specify error behavior or performance characteristics. No contradiction with annotations since none exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear sections (用途, 配合, Args, Returns, 场景) but somewhat verbose with emojis and formatting. Every sentence adds value, though some redundancy exists between '主要用途' and '推荐使用场景'. Front-loaded with core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 3 parameters with 0% schema coverage and no annotations, the description provides comprehensive context: clear purpose, usage guidelines, parameter explanations, return value indication, and workflow integration. The output schema exists, so return values don't need detailed explanation in the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates by explaining all three parameters in Chinese: filename (optional, auto-generated timestamp), full_page (complete page vs visible area), and element_selector (specific element only). It adds meaningful context beyond basic schema titles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as '截取页面截图' (take page screenshot) and positions it as '标准化工作流程第1步' (standardized workflow step 1). It distinguishes from siblings by emphasizing visual confirmation before element operations, unlike text-based tools like get_page_text or get_dom_tree.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance is provided with '推荐使用场景' (recommended usage scenarios) listing specific situations like after page navigation and before clicks/inputs. It also explains tool coordination with multimodal vs non-multimodal LLM workflows, clearly differentiating when to use this versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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