search_foods

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

Annotations already establish the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the bar is lower. The description adds useful behavioral context beyond annotations: results contain food IDs, measure_ids, and source information, and matching is by name/keyword. There is no contradiction between the description and annotations.

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?

Every sentence earns its place: purpose, return shape, downstream routing, then the parameter definition. The purpose is front-loaded in the first sentence, and the entire description is compact with zero fluff.

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 low-complexity, single-parameter, read-only search tool with an output schema and rich annotations, the description is complete. It covers what the tool does, what results contain, how to chain results into add_food_entry or get_food_details, and what the query parameter means. Minor details like pagination or result limits are not critical at this level of simplicity.

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 0%, so the description must fully compensate — and it does. The Args block defines query as a 'Food name or keyword' and supplies concrete examples ('eggs', 'chicken breast'), adding real meaning that the bare string parameter in the schema completely lacks.

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 opening sentence, 'Search Cronometer's food database by name,' states a specific verb, resource, and scope in a single line. The follow-up about returning food IDs and source information, plus the routing to add_food_entry and get_food_details, distinguishes it from sibling listing and retrieval tools such as list_custom_foods and find_entries_by_food.

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 gives explicit downstream workflow guidance: use the returned food_id and measure_id with add_food_entry, or pass food_id to get_food_details for full nutrition info. It implies the public-database scope and separates this tool from detail-fetching tools, but it never explicitly states when not to use it (e.g., for custom foods, use list_custom_foods), leaving a small gap.

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