Identify the function type of a transform (e.g., PythonLocal, PEL, Optimize) by reading its Function field from the provided transform path.
Get the Transform's Function type (e.g. 'PythonLocal', 'PEL', 'Optimize'). This reads the 'Function' child field.
| Name | Required | Description | Default |
|---|---|---|---|
| transform_path | Yes | Transform path |
Changes observed during successful MCP inspections.
v0.2.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It explicitly states that this 'reads' the 'Function' child field, signaling a read-only operation, and the examples clarify the kind of values returned. It does not cover edge cases or errors, but for a simple getter this is adequate.
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 two short, efficient sentences. It front-loads the core purpose, adds clarifying examples, and includes one implementation detail that helps confirm the behavior. No filler or redundant information.
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?
Given the tool's low complexity—one required parameter, no nested objects, no output schema—the description is sufficient. It states what is retrieved, where the value comes from, and provides examples of possible values, leaving only minor edge-case information unstated.
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?
The schema already describes the single parameter at 100% coverage ('Transform path'), so the baseline is 3. The description adds context by linking the path to a Transform and indicating the target is a child field, but it does not provide deeper format, syntax, or path-pattern details beyond the schema.
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 uses a specific verb ('Get') and resource ('the Transform's Function type') with concrete examples ('PythonLocal', 'PEL', 'Optimize'). It also identifies the underlying source field. However, it does not explicitly distinguish itself from sibling tools like transform_get_funcdict or transform_get_fields, so the differentiation is implied rather than stated.
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 makes the main use case clear: retrieve the Function type of a Transform by reading the 'Function' child field. However, it does not mention alternatives, exclusions, or specific conditions for choosing this tool over related transform getter tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.