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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds genuine behavioral context by narrowing the payload to 'food_id and name only', which tells the agent this cannot satisfy nutrition lookups and should be followed by get_food_nutrition — useful routing signal beyond structured data.

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?

Three short sentences, zero filler, with purpose leading, usage condition second, and return scope last. Every sentence carries distinct information.

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?

An output schema exists, so return values need not be re-explained, and annotations cover the safety profile. Purpose, trigger condition, and payload scope are all present for a simple two-parameter read tool — nothing an agent needs to call it correctly is missing.

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 description coverage is 100%, so both the limit and query parameters are already documented. The description restates 'partial food name' but adds no syntax, format, or matching-behavior detail beyond the schema — baseline 3 applies.

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?

States a specific verb+resource: 'Typeahead suggestions for a partial food name.' The 'partial/incomplete' framing implicitly distinguishes it from search_foods, but no sibling is named explicitly, so full differentiation relies on the agent inferring the contrast.

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?

'Use when the name is incomplete' gives a clear triggering condition, which is strong context for a suggestion endpoint. It stops short of explicitly naming search_foods as the alternative for complete names or full-text queries, so the routing rule is implied rather than stated.

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