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

With no annotations provided, the description carries the full burden. It discloses the volume cap (50 per day) and the nature of the data (public profile, contact channels, what is included). However, it does not disclose what happens when the slug is invalid or not found, whether the response includes any internal fields, or the exact structure of the returned profile. The description adds some behavioral context but lacks details on error handling or edge cases.

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, front-loaded with the tool's core purpose and critical usage details. Every sentence adds value: the first defines what and how to call it, the second sets expectations about scope and rate limits. No wasted words, and the structure is easy 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?

Given the single parameter, complete schema coverage, and no output schema, the description is nearly complete. It covers the purpose, how to get the parameter, what data to expect, and a critical constraint (volume cap). The only missing context is error behavior and response format details, but for a simple tool with no output schema, the description suffices 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?

Schema coverage is 100% with one parameter (slug) already described with an example. The description adds value by explaining what a slug is (the last path segment of a findmyfarmer.ca URL) and that it's also returned by search_farms, which is not in the schema. This helps the agent understand how to obtain and format the parameter, so it earns a baseline of 3 with a slight positive contribution.

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 fetches a farm's full public profile by URL slug, with specific examples of what is included. It distinguishes itself from siblings like search_farms by focusing on a single farm's profile and from list_places by emphasizing the farm-specific context. The verb 'fetch' and resource 'one farm's full public profile' are specific and unambiguous.

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 explains when to use this tool: to retrieve a specific farm's complete public profile, using the slug obtained from search_farms or the URL. It also implies it is not for bulk access by mentioning the volume cap and that it serves reference use. The context of when to use it versus alternatives is clear from the definition of the slug's source.

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