recommend_robot_mower

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

Annotations are absent, so the description carries the full burden of disclosing behavior. It indicates a recommendation action but does not state that it is read-only (no side effects), does not explain how the recommendation is computed, and does not mention what happens when no mower matches the criteria. The word 'recommend' implies non-mutating, but this is not explicitly stated.

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, front-loaded sentence that states the purpose first and then lists the key inputs. There is no fluff or redundancy; every word contributes to understanding the tool's function.

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 no output schema and no annotations, the description should explain what the tool returns (e.g., a ranked list, a single top pick, or a set of options). It does not describe the output format, nor does it mention edge cases like oversized yards or incompatible slopes. An agent cannot fully anticipate the tool's behavior beyond the basic recommendation intent.

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 baseline is 3. The description rephrases the parameters ('lawn size', 'slope', 'budget', 'obstacle avoidance') without adding new meaning beyond the schema's own parameter descriptions. It does not clarify units or format, but the schema already covers those (e.g., slope in percent grade, budget in USD).

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 states a specific verb (recommend), a resource (robot lawn mowers), and the context (best-fitting for a specific yard). It clearly differentiates from siblings: list_robot_mowers (listing), get_robot_mower (retrieving one), and compare_robot_mowers (comparing) – this tool produces a tailored recommendation based on yard parameters.

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 tells the agent what inputs to provide (lawn size, optional slope, budget, obstacle avoidance) but does not explicitly state when to use this tool versus its siblings. It implies it is for recommendation scenarios, but there is no exclusion guidance such as 'use list_robot_mowers to browse all models' or 'use compare_robot_mowers for side-by-side comparisons.'

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