query_ifc_elements

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

With no annotations, the description carries full behavioral burden. It does not disclose return type, pagination behavior, or whether the tool reads-only or has side effects, and limit parameter behavior is unmentioned.

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?

Two sentences with no redundant words; front-loads the verb and resource, then provides a helpful example. Excellent economy.

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 5 parameters, no annotations, and an output schema, the description should clarify what the tool returns and how filters interact. It leaves critical behavioral gaps, making the tool under-specified for autonomous selection and invocation.

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 description maps 'type, storey, or properties' to element_type, storey, and property_filter, giving some meaning. However, it does not explain the property_filter syntax or the limit parameter, and ifc_path is not elaborated.

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 'Search/filter IFC elements by type, storey, or properties' and gives a concrete example. This distinguishes it from sibling tools like get_ifc_statistics and list_ifc_spaces.

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 example 'How many fire doors on Level 2?' provides a clear use case for querying filtered data. It does not explicitly name alternatives, but the intended context is evident from the query language.

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