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

Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds valuable behavioral context by stating the return content (metadata, update dates, canonical URLs) and explicitly ruling out private learner data access. This goes beyond the annotation hints and gives the agent clear expectations about side effects and data boundaries.

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 a single, well-structured sentence that front-loads the core purpose, then efficiently adds return-type and privacy information. There is no redundant or filler content, and the extra detail is directly relevant to an agent's decision-making. The minor typo 'Drivings' does not detract from clarity.

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?

With an output schema present, the description does not need to detail return structure, but it still provides a summary of returned fields (metadata, update dates, URLs) and the non-access to private data. It also covers the main user intent (search by topic/question) and is sufficient given the tool's low complexity. Lacks mention of pagination or sorting, but these are not necessary for basic usage.

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 description coverage is 0%, so the description was expected to compensate. It explains that the query parameter can be a topic or question, which adds some semantic meaning, but it does not mention the required 'region' parameter or the optional 'limit' parameter. The schema's enum values (uk/us) and limits are self-explanatory, yet the description still leaves the purpose of region and the tuning behavior of limit to inference.

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's purpose with a specific verb ('Search'), a defined resource ('published driving guides'), and the search mechanism ('by topic or question'). It also distinguishes itself from sibling tools by specifying that it returns concise metadata rather than full guide content, and explicitly notes it does not access private learner data.

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 use when the agent needs to find guides by topic or question, and the boundary 'does not access private learner data' provides a clear exclusion. It does not explicitly name sibling tools or state 'use this instead of X', but the context of sibling tools (e.g., 'get_driving_guide') strongly implies the search-for-listing versus retrieve-specific-guide distinction.

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