get_model_schema

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

With no annotations available, the description carries the behavioral disclosure burden, and it does convey that the tool retrieves the model definition in TMSL format, parses the structure, and returns a dictionary. However, it omits details about error behavior, permissions, and how omitted parameters are resolved in the current context, so the disclosure is only partial.

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 well structured with a clear opening statement, a short implementation note, an Args section, and a Returns section. It is slightly redundant because the components 'tables, columns, measures, and relationships' appear in both the first sentence and the Returns line, but overall the text is focused and efficient.

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 read-only schema retrieval tool, the description adequately covers the main action, optional inputs, and the general shape of the return value. It is less complete because it gives no usage guidance, no error or failure behavior, and no explanation of how the optional workspace and model parameters resolve relative to the current context.

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 input schema has zero parameter descriptions, so the Args block is important and does add that workspace and model are optional 'Name or ID' values. It does not explain how the parameters interact with context or how the optionality is resolved, and it lists 'ctx' as an argument even though ctx is not present in the input 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 clearly identifies the operation as retrieving the complete schema of a semantic model and enumerates the included components: tables, columns, measures, and relationships. However, it does not explicitly differentiate itself from the sibling tool 'get_semantic_model', leaving some ambiguity about which tool returns what.

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 when-to-use or when-not-to-use guidance, and no mention of alternatives such as 'get_semantic_model', 'list_semantic_models', or 'table_schema'. The description states what the tool does but gives no assistance in selecting it over the many related sibling tools.

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