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

With no annotations, the description carries the full burden of behavioral disclosure. It only says 'Search the Farmdex' and gives examples, but does not describe what kind of results are returned (e.g., list of matches, exact matches, suggestions), any pagination or limits, or whether it's a read-only operation. For a search tool, this is a notable gap.

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?

Two sentences, zero wasted words. The action and scope are front-loaded, and the usage context follows naturally. It is model and easy to parse.

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?

For a tool with a single parameter and no output schema, the description gives enough purpose and usage context. It hints at the differentiation from search_farms. However, it does not explicitly contrast with other knowledge-related siblings like define_term or get_species, which could help an agent choose correctly. Still, the core details are sufficient for a simple search tool.

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 parameter 'query' is already documented with an example. The description adds context by listing what kinds of things can be searched (categories, species, variants, heritage varieties, livestock breeds), which slightly enriches the meaning beyond the schema's bare example. This aligns with the baseline of 3 for high 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 a specific verb ('Search') and resource ('Farmdex — agricultural knowledge database of categories, species, and variants'), with concrete examples. It also differentiates from sibling tools by positioning it as a pre-step to farm searching, making it distinguishable from search_farms and other knowledge 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?

It provides clear context on when to use it: 'resolving what a food product actually is before searching for farms that sell it.' This implicitly tells the agent when to prefer this over search_farms. However, it does not explicitly name alternatives or state when not to use it, so it falls short of perfect guidance.

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