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

Annotations provide readOnlyHint=true, and the description adds meaningful context about what the call returns: protein, W strength, hydration curve, maturation profiles, and description. This goes beyond the annotation's safety signal and gives the agent a concrete expectation of the response. No contradictions are present.

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, tightly-worded sentence with the key action and object front-loaded. Every phrase earns its place, and it avoids redundant or padded language.

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 one-parameter read-only lookup tool, the description is complete: it names the input (slug), the action, and the expected output fields. Since there is no output schema, the explicit list of return content compensates well, and the readOnlyHint annotation covers the behavioral safety profile.

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%, and the schema already documents the slug parameter with format guidance and examples. The description only repeats 'by its slug,' adding no new parameter semantics beyond what is already structured in the input schema.

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 clear action ('Get detailed information') on a specific resource ('a specific flour by its slug'), and lists the returned data fields, making the tool's purpose immediately obvious. It does not explicitly name or differentiate from the sibling search_flours tool, but the 'by its slug' qualifier implies a direct-lookup use case that is distinct from searching.

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 implies when to use it: when you already know a flour's slug and need detailed data. However, it does not explicitly state when not to use it or mention search_flours as the alternative for discovering slugs, so usage guidance is mostly inferred rather than stated.

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