query_analytical_data

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

With no annotations, the description carries the full burden for behavioral disclosure. It explains query capabilities but does not mention whether the operation is read-only, potential side effects, authentication requirements, rate limits, or performance implications. The read-only nature of a query is assumed but not stated, and there is no disclosure of limitations or error behavior.

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 three sentences: the first states the core purpose, the second lists supported OData syntax, and the third mentions typical use cases. Every sentence contributes information without redundancy or fluff, and it is well-structured with the most critical information front-loaded.

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?

The description covers the tool's main function and query syntax, but lacks key contextual details: there is no output schema, and the description does not specify the response format or structure of returned data. It also does not explain the relationship between space_id, asset_id, and entity_set, which are required parameters. For a tool with 10 parameters and no output schema, this leaves some gaps for an agent trying to use it correctly.

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 100%, and each parameter has a detailed description. The description adds semantic value by mapping parameters to OData query concepts ($select, $filter, $orderby, $top/$skip, $apply), which helps an agent understand how to combine parameters. While the schema already includes examples, the description provides a cohesive syntax overview that goes beyond individual parameter documentation.

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?

Description clearly states it executes OData queries on analytical models to retrieve aggregated data with dimensions and measures. The verb+resource combination ('Execute OData queries on analytical models') distinguishes it from relational query tools like query_relational_entity and generic tools like execute_query. Listing supported OData syntax reinforces the specific purpose.

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 implies usage context by mentioning business intelligence, reporting, and data analysis, but it does not explicitly state when to use this tool versus alternatives (e.g., query_relational_entity for relational data or execute_query for SQL). No exclusions or alternative tool references are provided, so guidance is implied rather than direct.

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