Skip to main content
Glama

get_video_metadata

Extract video metadata including format, duration, resolution, and codec information from video files for analysis and processing.

Instructions

Function to extract metadata of the given input video.

Params: input_video_path (str): Path to the input video.

Returns: JSON of the video metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_video_pathYes
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 of behavioral disclosure. It mentions the tool 'extracts metadata' and returns JSON, but lacks details on what metadata is included (e.g., duration, resolution, codec), whether it's read-only (implied but not stated), error handling for invalid paths, or performance considerations. For a tool with no annotations, this is a significant gap in behavioral context.

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?

The description is appropriately sized and front-loaded, starting with the core purpose. The structure with 'Params:' and 'Returns:' sections is clear, though slightly verbose. Every sentence earns its place by defining purpose, parameter, and return value, with no wasted text.

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 complexity (a metadata extraction tool with no annotations, 0% schema coverage, and no output schema), the description is incomplete. It doesn't explain what metadata is extracted, error conditions, or output format details beyond 'JSON.' For a tool with such sparse structured data, more context is needed to be fully 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?

The description adds minimal meaning beyond the input schema. It specifies that input_video_path is a 'Path to the input video,' which slightly clarifies the schema's 'Input Video Path' title. However, with 0% schema description coverage, the description doesn't compensate by explaining path format (e.g., local file, URL), supported video types, or constraints. The baseline is 3 due to schema coverage being low but the description adding some value.

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 as 'extract metadata of the given input video' with a specific verb ('extract') and resource ('video metadata'). It distinguishes from siblings like clip_video or extract_frames by focusing on metadata extraction rather than video manipulation or content extraction. However, it doesn't explicitly contrast with all siblings (e.g., get_normalized_clips might also involve metadata).

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is appropriate (e.g., for analyzing video properties) or when to choose other tools (e.g., use extract_frames for frame data, extract_audio for audio extraction). The context is implied but not stated explicitly.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/yubraaj11/ffmpeg-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server