transform_get_length

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

With no annotations, the description carries the full burden of behavioral disclosure. It does add one useful trait: 'Returns 0 for an empty dataset.' However, it does not mention behavior for invalid or nonexistent transform paths, whether it errors, or any other edge cases. It is minimally transparent but not rich.

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 a single concise sentence, front-loaded with the main verb and object, with a brief edge-case note appended. There is no filler, repetition, or unnecessary detail.

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?

For a single-parameter getter with no output schema, the description covers the core function and the most important edge case. It does not state prerequisites (e.g., that the transform must exist or have been executed) or explicitly differentiate from sibling get_length tools, but these are minor gaps for such a simple 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?

The schema has 100% description coverage for the only parameter (transform_path), so the baseline is 3. The tool description adds no additional meaning or context to the parameter beyond what the schema already provides.

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 states a specific verb ('Get') and a clear resource ('the number of data points in the Transform's dataset'). The added empty-dataset behavior reinforces exactly what is counted. It is distinguishable from sibling get_length tools by the explicit 'Transform's dataset' scope.

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?

No guidance is given about when to use this tool over sibling get_length tools such as input_get_length, output_get_length, or setup_get_length. There are no exclusions, prerequisites, or alternative routing instructions. Usage is only implied by the tool name and resource.

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