search_food

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

With no annotations, the description carries the burden. It discloses the fuzzy search behavior and score-based sorting, and explains the data source. It does not explicitly state read-only behavior, but for a search tool this is implied; the added purpose gives useful context.

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: first the action and output, second the purpose. It is concise, front-loaded, and contains no unnecessary words.

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 simple search tool with an output schema, the description is complete. It covers the domain, matching behavior, and intended use case. There is no need to explain return values since the output schema exists.

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?

The schema already documents both parameters (keyword, limit) with 100% coverage. The description adds value by clarifying that the search is fuzzy by food name and scoped to the food composition table, giving more meaning to the keyword parameter beyond the schema's generic 'food keyword'.

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 identifies the tool's action (fuzzy search food by name), the specific resource (China Food Composition Table), and the output (candidates sorted by score). It distinguishes itself from sibling tools like find_substitutes or can_eat by focusing on name lookup/verification.

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 provides a clear use case: confirming what a parent's mentioned food is called in the composition table and verifying the correct entry. It does not explicitly mention when not to use the tool or name alternative tools, but the context is sufficient for selection.

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