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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely non-obvious behavior: ideas rotate daily, weight-loss asks get lighter ideas capped at 450 calories with a doctor/dietitian pointer and no shop links, and it refuses to set calorie or weight targets. It does not describe the shape of a returned idea beyond 'rough macros'.

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?

Front-loads purpose, then examples, then valid values, then the exception policy; every sentence carries information. It loses a point for duplicating the title verbatim and re-listing the goal/diet/meal values that the schema already enumerates.

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?

With six optional parameters, no output schema, and only read-only annotations, the description covers what an agent needs: how to fill each axis, when to fall back to q, the daily rotation, and the special handling of weight-loss requests. Return-shape detail is not required given 'rough macros' is disclosed.

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 baseline is 3, but the description adds real semantics: q is an alternative to the structured filters, country controls which shop links appear (US/GB/IE get local Amazon links) and defaults from the request, and the accepted goal/diet/meal vocabularies are restated for quick selection.

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 concrete verb (generate/return ideas) and resource (meal ideas) plus the axes it varies on: goal, diet, meal, with rough macros. It is clearly distinguishable from siblings platepal_get_food_nutrition and platepal_get_barcode_nutrition, which look up nutrition facts rather than propose meals.

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?

Gives three concrete invocation examples ('high protein halal dinner idea', 'quick vegan lunch', 'cheap vegetarian breakfast ideas') and explains the q fallback for free-form user wording, plus a specific rule for weight-loss requests. It never explicitly rules out use cases or names a sibling alternative (e.g. use get_food_nutrition for per-item nutrition), so guidance is clear but not exhaustive.

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