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MCP Feedback Collector

by keizman

pick_image

Select images from your device or paste from clipboard to provide visual feedback in AI assistant interactions.

Instructions

弹出图片选择对话框,让用户选择图片文件或从剪贴板粘贴图片。 用户可以选择本地图片文件,或者先截图到剪贴板然后粘贴。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'pick_image' tool. It is decorated with @mcp.tool() which also serves as registration. Opens a tkinter file dialog to let user pick an image file, encodes it to base64, and returns an MCPImage object.
    @mcp.tool()
    def pick_image() -> MCPImage:
        """
        弹出图片选择对话框,让用户选择图片文件或从剪贴板粘贴图片。
        用户可以选择本地图片文件,或者先截图到剪贴板然后粘贴。
        """
        root = tk.Tk()
        root.withdraw()  # 隐藏主窗口
        
        file_types = [
            ("图片文件", "*.png *.jpg *.jpeg *.gif *.bmp *.webp"),
            ("PNG files", "*.png"),
            ("JPEG files", "*.jpg *.jpeg"),
            ("所有文件", "*.*")
        ]
        
        file_path = filedialog.askopenfilename(
            title="选择图片文件",
            filetypes=file_types
        )
        
        root.destroy()
        
        if file_path:
            try:
                with open(file_path, "rb") as f:
                    image_data = f.read()
                    image_base64 = base64.b64encode(image_data).decode('utf-8')
                    
                    return MCPImage(
                        data=image_base64,
                        media_type="image/png"
                    )
            except Exception as e:
                raise Exception(f"读取图片失败: {str(e)}")
        else:
            raise Exception("未选择图片文件")
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It describes the tool's behavior as popping up a dialog for user interaction, which is useful. However, it doesn't disclose critical traits like whether this is a blocking operation, what happens on user cancellation, error handling, or UI constraints (e.g., supported image formats). For a user-interactive tool with zero annotation coverage, this is a significant gap.

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

Conciseness5/5

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

The description is concise and well-structured: two sentences that clearly state the tool's function and user options. Every sentence adds value without redundancy, making it front-loaded and easy to understand.

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

Completeness2/5

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

Given the tool's complexity (user-interactive dialog) and lack of annotations or output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., image data, file path, or error), how it handles edge cases, or any dependencies. For a tool with no structured data to supplement, this leaves key contextual gaps.

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?

The input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description appropriately doesn't discuss parameters, which is efficient. Baseline is 4 for 0 parameters, as it avoids unnecessary details.

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

Purpose4/5

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

The description clearly states the tool's purpose: '弹出图片选择对话框,让用户选择图片文件或从剪贴板粘贴图片' (pop up an image selection dialog to let users choose image files or paste from clipboard). It specifies the action (pop up dialog) and resource (image files/clipboard images), though it doesn't explicitly differentiate from sibling tools like 'get_image_info' or 'collect_feedback'.

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

Usage Guidelines3/5

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

The description implies usage context by mentioning '用户可以选择本地图片文件,或者先截图到剪贴板然后粘贴' (users can choose local image files or first screenshot to clipboard then paste), suggesting when to use it for image input. However, it lacks explicit guidance on when to use this vs. alternatives like 'get_image_info' (which might retrieve image metadata) or 'collect_feedback' (which might involve user input beyond images).

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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