pbi_get_object

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

With no annotations provided, the description carries the burden of disclosing behavior. It adds useful behavior for measures (inclusion of DAX references), but it does not state that the operation is read-only, whether errors occur for invalid names, or what 'all detail' includes. This is a partial disclosure.

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 brief and front-loaded, with a clear main statement followed by a compact list of kind specifics. Every sentence adds value, and the structure is easy to scan.

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 has an output schema, return values need not be described. The required parameters are covered well, and the tool is simple (3 params, 2 required). The only notable omission is the 'source' parameter, which is optional with a default, so overall completeness is high but not perfect.

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 coverage is 0%, so the description must explain parameters. It explains 'kind' allowed values and the column naming format, and clarifies that 'name' uses 'Table[Column]' for columns. However, the 'source' parameter (optional, default 'live') is not mentioned, leaving a gap.

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 states the tool returns a model object with all its detail ('Devuelve un objeto del modelo con todo su detalle') and specifies supported kinds (table, column, measure). It is distinct from sibling tools like pbi_list_tables or pbi_get_visual, though it does not explicitly differentiate itself.

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?

Implied usage: the description indicates you specify a kind and name, with a naming convention for columns ('Tabla[Columna]') and notes that measures include DAX references. However, it lacks explicit guidance on when to prefer this tool over other model-inspection tools like pbi_measure_dependencies or pbi_list_partitions.

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