search_trains_by_name

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

No annotations are provided, so the description carries the full burden. It usefully discloses partial-match behavior and gives examples, but it does not describe result limits, case sensitivity, pagination, or what the response contains.

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?

A single efficient sentence with the core action and matching mode front-loaded. The examples add clarity without bloating the definition.

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 simple one-parameter search tool with no output schema, the description is sufficient to invoke it correctly. It leaves out return-shape and result-limit details, which are minor but would help an agent understand what to expect.

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%, so the single parameter is already documented as a train name with a two-character minimum. The description adds partial-match semantics and examples, but no additional formatting or matching details beyond the 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?

States a specific verb and resource: search Indian Railways trains by train name query. The partial-match examples (“Rajdhani”, “Shatabdi”, etc.) make clear this is name-based lookup, distinguishing it from get_train_by_number.

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 when to use it by specifying name-query partial matching, but it does not explicitly contrast with sibling tools such as search_trains or get_train_by_number. An agent can infer the use case, but alternatives are not routed.

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