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

Annotations already indicate readOnly and idempotent behavior. The description adds meaningful behavioral context: returns up to 3 matching guides, lists the fields returned (title, excerpt, difficulty, reading time, URL), and mentions the 24+ articles. This provides transparency about result limits and content type beyond the 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 two sentences plus an example, with all information front-loaded. It efficiently conveys the resource, result format, usage context, and examples without redundancy. Every sentence earns its place.

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 low complexity and the presence of an output schema, the description is complete. It covers purpose, usage, result limits, and return fields. No additional context is needed for an agent to invoke it 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?

The input schema already covers both parameters with clear descriptions (query and limit). The description provides example query values but does not add significant semantic meaning beyond the schema. Baseline of 3 is appropriate given 100% schema coverage.

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 Cyclesite's expert buying guides, a specific resource. It distinguishes this from siblings like get_size_guide or get_spec_sheet by focusing on buying guides with journalistic content. The verb 'search' is specific and the scope is well-defined.

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 explicitly says 'Use for educational queries that don't need live inventory,' providing clear context and excluding use cases for inventory-based tools. It also gives concrete example queries that illustrate when to use the tool. This effectively guides selection among the sibling tools like search_bikes or get_listing_detail.

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