output_get_data

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 reveals the return type as a dictionary but says nothing about whether the output dataset must already exist, what keys or structure the dictionary will have, how the msb and imag parameters affect behavior, or whether the operation has side effects.

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 sentence with no filler and the core operation is front-loaded. It earns conciseness points, though the brevity comes at the expense of essential supporting 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?

There is no output schema and no annotations, and the sibling set includes close alternatives like output_get_df and output_get_field, so the description needs to explain more. It does not cover the dictionary structure, parameter meanings, or usage context, making it barely adequate for simple default calls but insufficient for correct parameter selection.

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?

Schema description coverage is 0%, so the description must compensate, but it explains none of the three parameters. output_path is somewhat inferable from the word 'dataset,' while msb (M/S/B) and imag remain entirely unexplained, leaving the agent unable to decide how to set them correctly.

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 and resource: 'Get Output dataset as dictionary.' It clearly identifies the tool as retrieving an output dataset, and the 'as dictionary' phrasing differentiates it from likely siblings like output_get_df and output_get_field. However, it doesn't explicitly name sibling tools to sharpen the differentiation.

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?

There is no guidance on when to use this tool versus alternatives such as output_get_df, output_get_field, or output_get_modedict. The description only implies it is for obtaining a dictionary representation, with no exclusions or selection criteria provided.

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