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inpaint

Remove or replace objects in images using AI inpainting to edit visual content by specifying what to change with text prompts.

Instructions

Remove or replace objects in an image using AI inpainting. Cost: $0.15. Requires Tier 1+.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
media_urlYesURL of the image to edit
promptYesWhat to remove, replace, or change in the image
mask_urlNoOptional mask image URL (white = edit area, black = keep)

Implementation Reference

  • The handle_tools_call function routes tool calls, including logic for video generation. It does not contain an implementation for 'inpaint', suggesting the tool may not exist or is handled generically via the API.
    def handle_tools_call(params: Dict) -> Dict:
        """
        Handle tools/call request.
    
        Directive #240: Special handlers for video tools.
        """
        tool_name = params.get("name", "")
        arguments = params.get("arguments", {})
    
        # ═══════════════════════════════════════════════════════════════════
        # VIDEO TOOL HANDLERS (Directive #240)
        # ═══════════════════════════════════════════════════════════════════
    
        if tool_name == "generate_video":
            return _handle_generate_video(arguments)
    
        if tool_name == "estimate_video_cost":
            return _handle_estimate_video_cost(arguments)
    
        if tool_name == "get_task":
            return _handle_get_task(arguments)
    
        # Default: forward to MCP API
        response = make_request("/tools/call", {
            "name": tool_name,
            "arguments": arguments
        })
        return response
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 adds valuable behavioral context: it discloses the monetary cost ($0.15) and access requirements (Tier 1+), which are crucial for usage decisions. However, it doesn't mention rate limits, response format, or error conditions.

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 extremely concise with just two sentences that each earn their place: the first explains the core functionality, and the second provides critical operational constraints (cost and requirements). No wasted words or redundant information.

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

Completeness3/5

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

For a mutation tool with no annotations and no output schema, the description covers the basic purpose and constraints well but lacks information about what the tool returns (e.g., edited image URL, status) and potential side effects. Given the complexity of image editing, more output information would be helpful.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 for high schema coverage.

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 with specific verbs ('remove or replace objects') and identifies the resource ('image') and method ('AI inpainting'). It distinguishes from siblings like 'background_remove' (specific background removal) and 'ai_edit' (broader editing) by focusing on object-level inpainting.

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 for object removal/replacement in images, but doesn't explicitly state when to use this versus alternatives like 'background_remove' (for backgrounds only) or 'ai_edit' (for general edits). It mentions cost and tier requirements, which provide some context but not comparative guidance.

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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