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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, fully covering the safety profile. The description adds the non-deterministic random behavior, the one-or-more count range, and the source directory, which are valuable 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 a single sentence with the main action front-loaded and compact use-case context. There is slight redundancy in mentioning 'Open Brewery DB' twice, but it remains efficient and scannable.

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 one optional parameter, a detailed schema, a provided output schema, and comprehensive annotations, nothing critical is missing. The description addresses randomness, result count, source, and typical use cases; return structure is covered by the output schema.

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 single 'size' parameter is fully described in the input schema (default 1, max 50, with bounds), so the description doesn't need to elaborate. At 100% schema coverage, the baseline of 3 is appropriate, and the description correctly omits redundant parameter detail.

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 opens with the specific verb 'Get' and names the exact resource ('one or more random breweries from the Open Brewery DB directory'), making the action unmistakable. The use cases (discovery, demos, sampling) further clarify its niche relative to sibling openbrewery list/search tools.

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 clearly states when to use the tool—discovery, demos, or sampling—which gives an agent context for selection. It does not explicitly name alternatives or exclusions, but the 'random' qualifier makes the boundary with list/search obvious.

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