understand_image

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

Since no annotations are provided, the description carries the full burden. It discloses supported input types (local paths, HTTP(S) URLs, image data URLs), built-in prompt modes, and optional ASCII rendering. It also communicates that this is a fallback for native vision, providing valuable behavioral context beyond the schema.

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

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

The description is front-loaded with the critical usage warning, and the second paragraph efficiently lists capabilities and input types. While the first paragraph is slightly verbose, every sentence contributes meaning, and the structure is clear.

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

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

With 11 parameters, no output schema, and no annotations, the description is insufficiently complete. It does not explain what the tool returns, how the modes differ, or how to combine parameters. The broad capability list is helpful but leaves many operational details unaddressed for such a complex tool.

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

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

Schema description coverage is 0%, so the description must compensate. It only hints at two parameters ('Built-in prompt modes' and 'optional ASCII rendering') but does not explain the modes, detail levels, image input parameters, or other fields. The description does not provide enough information to know how to populate the 11 parameters effectively.

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

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

The description clearly states the tool 'Understand one or more images' with a specific list of use cases (description, OCR, document extraction, UI inspection, chart reading, code screenshots). However, it does not differentiate from the sibling tool 'analyze_image', so it lacks sibling distinction.

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

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

The description provides explicit instructions: 'DO NOT CALL if you natively support vision and can access the supplied image directly' and 'Call this MCP only when native vision is unavailable, the image source is inaccessible... or the user explicitly requests this MCP.' This clearly specifies when to use and when not to use, including an alternative (native vision).

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