Skip to main content
Glama

describe_scene

Analyze an image to get a detailed scene description, covering spatial relationships, atmosphere, and context. Optionally focus on specific elements like people or architecture.

Instructions

Get a detailed description of a scene, including spatial relationships, atmosphere, and context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusNoWhat to focus the description on (e.g., 'people', 'architecture', 'nature')
imageYesEither a URL to the image or base64-encoded image data
Behavior2/5

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

With no annotations provided, the description alone must disclose behavior. It reveals that the output will include spatial relationships, atmosphere, and context, but omits any details about output format, potential limits, errors, or differences from analyzing generic images. This is insufficient for a tool with no structured behavioral cues.

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 a single, front-loaded sentence that efficiently conveys the tool's purpose and key outputs without redundant filler. Every phrase earns its place.

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?

The tool is relatively simple with two parameters and no output schema. The description provides a reasonable overview of what the description will contain, but lacks guidance on result format or examples. Given the existence of overlapping siblings, more context on when exactly to use this tool would be valuable.

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 schema already provides full descriptions for both parameters (image and focus), so the tool description adds no new parameter semantics. Baseline 3 applies because schema coverage is 100%, and the description's mention of scene context loosely complements the 'focus' parameter but adds no technical detail.

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 function: 'Get a detailed description of a scene' and specifies key content like spatial relationships, atmosphere, and context. This distinguishes it from generic image analysis and text extraction, though it does not explicitly name alternatives.

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 use when a scene-level description is needed, but gives no explicit guidance on when to prefer this over siblings like analyze_image. No exclusions or alternative conditions are mentioned, so usage context is only moderately clear.

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/cpramod/vision-mcp'

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