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video_merge

Combine multiple video clips into a single continuous video file. Merge videos from provided URLs in specified playback order for unified playback.

Instructions

Merge multiple video clips into one continuous video. Cost: $0.05. Requires Tier 1+.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
media_urlsYesURLs of videos to merge (in playback order)

Implementation Reference

  • The handler for video generation, which is the closest functionality to 'video_merge' available in the codebase, although 'video_merge' itself is not found.
    def _handle_generate_video(arguments: Dict) -> Dict:
        """
        Handle generate_video tool call (Directive #242: Veo 3.1).
    
        Creates a video generation task via V3 API.
        """
        prompt = arguments.get("prompt", "")
        duration = arguments.get("duration", 8)
        aspect_ratio = arguments.get("aspect_ratio", "16:9")
        generate_audio = arguments.get("generate_audio", True)
        resolution = arguments.get("resolution", "720p")
        negative_prompt = arguments.get("negative_prompt", "")
    
        if not prompt:
            return {
                "isError": True,
                "content": [{"type": "text", "text": "Error: prompt is required"}]
            }
    
        # Validate duration (Veo 3.1: 4, 6, 8 seconds)
        if duration not in (4, 6, 8):
            duration = 8
    
        # Validate aspect ratio (Veo 3.1: 16:9, 9:16)
        if aspect_ratio not in ("16:9", "9:16"):
            aspect_ratio = "16:9"
    
        # Validate resolution
        if resolution not in ("720p", "1080p"):
            resolution = "720p"
    
        # Create task via V3 API
        logger.info(f"Creating Veo 3.1 video task: duration={duration}s, audio={generate_audio}")
    
        params = {
            "prompt": prompt,
            "duration": duration,
            "aspect_ratio": aspect_ratio,
            "generate_audio": generate_audio,
            "resolution": resolution
        }
        if negative_prompt:
            params["negative_prompt"] = negative_prompt
    
        response = make_v3_request("/v3/tasks", {
            "type": "video",
            "params": params
        })
    
        if "error" in response:
            return {
                "isError": True,
                "content": [{"type": "text", "text": f"Error: {response['error']}"}]
            }
    
        # Format success response
        task_id = response.get("task_id", "unknown")
        cost_table = VIDEO_COSTS_WITH_AUDIO if generate_audio else VIDEO_COSTS_NO_AUDIO
        estimated_cost = response.get("estimated_cost", cost_table.get(duration, 4.80))
    
        return {
            "content": [{
                "type": "text",
                "text": f"Video generation task created (Veo 3.1)!\n\nTask ID: {task_id}\nDuration: {duration} seconds\nAspect Ratio: {aspect_ratio}\nResolution: {resolution}\nAudio: {'Yes' if generate_audio else 'No'}\nEstimated Cost: ${estimated_cost}\n\nUse get_task with this task_id to check status and get the video URL when complete."
            }]
        }
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively adds critical context beyond the schema: the cost ($0.05) and access requirement (Tier 1+), which are essential for an agent to understand usage constraints. However, it doesn't mention other behavioral traits like rate limits, output format, or error handling.

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 and front-loaded, consisting of just two sentences that directly state the tool's purpose and key constraints (cost and tier). Every word earns its place, with no redundant or vague language, making it highly efficient for an agent to parse.

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

Completeness4/5

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

Given the tool's moderate complexity (merging videos with cost and access constraints), no annotations, and no output schema, the description does well by covering the core purpose and key behavioral aspects. However, it lacks details on output (e.g., format, size) and error cases, leaving some gaps for the agent to infer or handle unexpectedly.

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 the single parameter (media_urls) with its type, description, and constraints. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score of 3 for adequate but no extra value.

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 specific action ('merge multiple video clips') and resource ('into one continuous video'), distinguishing it from sibling tools like video_trim (which edits rather than combines) and generate_video (which creates new content). It precisely communicates the tool's function without ambiguity.

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 through the mention of cost and tier requirements, suggesting it's for paid operations, but doesn't explicitly state when to use this versus alternatives like video_trim or generate_video. No guidance is provided on prerequisites beyond the tier requirement, leaving the agent to infer context from the tool name alone.

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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