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aamar-shahzad

MCP Screenshot Server

add_watermark

Add a text watermark to a screenshot or image by setting the text, color, opacity, position, and font size.

Instructions

Add a text watermark to the image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesWatermark text
colorNoText color#ffffff
opacityNoOpacity (0-255)
image_idYesID of the image
positionNoPosition of the watermarkbottom-right
font_sizeNoFont size

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesStatus message
image_idYesImage ID that was annotated

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
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 states the action but does not mention that it modifies the image in place, whether it is reversible, or any side effects such as overwriting existing watermarks. For a mutation tool with zero annotation coverage, this is a significant gap.

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 a single, concise sentence with no wasted words. It is appropriately sized, though it could include more useful information without losing conciseness. The structure is clear and front-loaded with the core action.

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 tool's complexity (6 parameters, 2 required, with defaults) and no annotations, the description is inadequate. It does not explain how parameters like opacity, position, or font_size affect the result, nor does it mention any behavioral context. Although an output schema exists, the description still lacks essential information about side effects or prerequisites for an agent to call it correctly.

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 coverage is 100%, with all six parameters having descriptions in the input schema. The description adds no extra meaning beyond what the schema already provides, so a baseline of 3 is appropriate. It does not compensate for any missing parameter context, but the schema itself is sufficient.

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 states the verb 'add' and the resource 'text watermark' on an image, making the core purpose clear. However, it does not differentiate from the sibling tool add_text, which also adds text to an image. The term 'watermark' provides some distinction but not explicit enough for an agent to reliably choose between the two.

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?

There is no guidance on when to use this tool versus alternatives like add_text or other annotation tools. The description provides no context for selection, leaving the agent to infer usage from the name alone.

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