Explain a food additive

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is covered. The description adds genuine behavioral context by disclosing the shape of the answer (function, risk level, sources) — valuable since there is no output schema. It stops short of noting data freshness or source recency.

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?

One sentence, front-loaded with the action, then the output contents, then the accepted input forms. No wasted 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 single-parameter read tool with annotations covering the safety profile, the description supplies the remaining need: what the response will contain. Only minor gaps remain (source recency, unknown-additive behavior).

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 single parameter is fully documented there, so the schema carries the load. The description's example formats (E250, sodium nitrite, Red 40, carrageenan) reinforce accepted input styles but add little beyond the schema's own examples. 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 (explains) and resource (food additive) and spells out exactly what the answer contains: function, risk level, and sources. The resource is distinct from siblings like analyze_label and check_food, though it never explicitly contrasts itself with them.

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?

Usage is implied by the phrasing 'by E-number or name', which tells the agent the accepted lookup keys, but there is no explicit when-to-use guidance or routing versus the sibling tools. Adequate but leaves selection to inference.

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