Skip to main content
Glama

transformation_builder

Build an ImageKit image/video transformation URL from a natural language description.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
srcNoOptional source image URL. If not provided, a default sample image is used.
queryYesNatural language description of the desired transformation (e.g. "resize to 800x600", "add blur and grayscale", "remove background").
fetch_url_to_checkNoWhether to verify the generated URL is accessible via CDN.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
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 only mentions building a URL, but does not disclose that the tool may perform network requests (e.g., via fetch_url_to_check), any authentication requirements, or side effects. This is a significant gap for an external-service tool.

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, focused sentence that states the tool's core purpose without any fluff. It is front-loaded with the key action and resource, making it easy for an agent to quickly grasp the tool's function.

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 description is minimal but the schema covers parameter details, and there is an output schema present. However, it does not mention the optional src parameter or the URL verification behavior, nor any limitations of the natural language processing. For a tool with no annotations, the description could provide more context to be fully self-sufficient.

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 schema already provides detailed descriptions for all three parameters (src, query, fetch_url_to_check). The description does not add additional semantic context beyond what the schema gives, so the baseline score of 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool's action (build), the resource (ImageKit image/video transformation URL), and the input (natural language description). This is a specific verb+resource description that differentiates it from the only sibling, search_docs, which is obviously unrelated.

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 usage context by specifying it builds transformation URLs from natural language, but it does not explicitly state when to prefer this tool over alternatives or mention any exclusions. With only one sibling (search_docs) that is clearly distinct, the usage is inferred rather than explicitly guided.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.