get_train_composition

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

The description adds context about the returned information (carriage order, equipment, track assignment) beyond the annotations which already indicate read-only, idempotent, and non-destructive behavior. No contradiction with annotations.

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 clear sections (purpose, args, examples, typical questions) and front-loaded with the main purpose. While somewhat lengthy, every sentence adds value; minor redundancy could be trimmed.

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's complexity and the presence of an output schema, the description covers all necessary aspects: purpose, parameter details, usage examples, and typical queries. It is comprehensive for an AI agent to select and invoke 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?

Despite 0% schema description coverage, the description thoroughly explains each parameter: train_number with examples, railway_company with allowed values, operation_date with default and usage note, show_details with three options. This fully compensates for the schema's lack of descriptions.

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 retrieves train composition and carriage order for Swiss trains, listing specific details like classes, sectors, equipment, and track assignment. It distinguishes from sibling tool `get_train_occupancy` by focusing on composition rather than occupancy.

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 explains when to use the tool with parameter defaults and examples, and lists typical questions it can answer. However, it does not explicitly state when not to use it or mention alternative tools, though the context of sibling tools makes this implicit.

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