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Image Caption

ImageCaption
Read-only

Image Caption: Image Caption generates natural language descriptions for uploaded image files. Upload a JPG, PNG, or GIF up to 5MB to receive an automated caption for alt text and media tagging. (Cost: 20 credits)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "image": "<image>"
    },
    "name": "ImageCaption"
  }
}

Input Schema

NameRequiredDescriptionDefault
imageYesUpload an image file to generate a caption (supported formats: JPG, PNG, GIF, max 5MB)

Output Schema

NameRequiredDescriptionDefault
dataNo
errorNoError message, null on success
statusNo"ok" on success

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds two genuinely useful facts beyond that: the 5MB/format constraint and the 20-credit cost, which matters for planning. It says nothing further about latency, failure modes, or caption quality, so it earns credit without being rich.

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?

Two sentences, front-loaded with purpose, followed by input constraints and cost. Minor waste from restating the title ('Image Caption: Image Caption generates...'), but otherwise every clause carries information.

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?

For a one-parameter, read-only tool with an output schema and full annotation coverage, the description supplies what the structured fields cannot: supported formats, size limit, intended use, and cost. Little else is needed 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 description coverage is 100% and the single parameter already documents supported formats and the 5MB cap, so the description's repetition of the same constraints adds no new semantic meaning. Baseline 3 is appropriate when the schema does all the work.

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?

States a specific verb and resource ('generates natural language descriptions for uploaded image files'), which is unambiguous on its own. It does not, however, distinguish itself from near siblings such as ImagetoText, FaceDetector, or NSFWImageDetector, so an agent must infer the boundary.

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

Usage Guidelines4/5

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

Gives clear intended use ('for alt text and media tagging') and the input conditions (JPG, PNG, or GIF up to 5MB), which is enough context to select it confidently. It stops short of naming an alternative or stating when not to use it.

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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