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

The description adds significant behavioral context beyond the annotations (readOnlyHint, openWorldHint, idempotentHint). It details the return format (one line per match with name, type, region, status URL), total match count, lack of pagination, and sorting priority, providing a complete picture of the tool's 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 concise at four sentences, with clear front-loading of the purpose. Each sentence adds necessary information without redundancy, making it easy for an AI agent to parse quickly.

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?

Despite the lack of an output schema, the description fully explains the return format and behavior, including edge cases like no pagination and sorting. Given the tool's complexity (text search with limit), the description is complete and actionable.

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?

Although the input schema already describes the parameters (query and limit) with 100% coverage, the description adds valuable semantics: it explains that the query is a substring search across multiple fields, that the limit is a maximum with no pagination, and that results starting with the query sort first. These details enhance the agent's understanding 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?

The description clearly states the tool searches UK level crossings by name, URL word, or region name using substring and case-insensitive matching. It distinguishes itself from sibling tools like busiest_today, crossings_near, and crossing_status by focusing on text-based searching.

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 that results are limited to the first `limit` matches with no pagination, advising users to narrow queries for different results. It also mentions sorting behavior for names starting with query. However, it does not explicitly state when not to use this tool (e.g., for status or location queries).

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