Get personalized meal recommendations

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

Annotations declare readOnlyHint=false, which is surprising for a "get" tool; the description resolves that by disclosing that ReceiptCal records a private analytics event, explaining the write side effect. That is meaningful behavior beyond the structured hints, though return format and result limits beyond "up to 20" are unstated.

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?

Two tight sentences with the core purpose front-loaded and no filler. It earns its length, though the side-effect sentence could be slightly more explicit about scope.

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 tool with 0% parameter coverage and no output schema, the description should explain what servings/max_minutes do and roughly what the response contains. It covers the ranking signals but omits any parameter guidance, leaving the agent to guess on inputs.

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% and there are two parameters (servings, max_minutes) with no description and no constraints explained. The description never mentions either parameter, so it fails to compensate for the schema gap at a point where it must.

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 and resource ("Get up to 20 personalized recommendations") and enumerates the ranking signals (pantry, safety constraints, food profile, learned memories), so the agent knows exactly what comes back. It does not, however, distinguish itself from the sibling get_recommendations, leaving the "personalized" vs plain recommendation distinction to inference.

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?

There is no when-to-use guidance, no prerequisites, and no mention of the near-identical sibling get_recommendations that an agent would need to disambiguate between. The description assumes the caller already knows the context.

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