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

Beyond the annotations (non-read-only, non-destructive, non-idempotent), the description adds a genuinely useful behavioral rule: duplicate foods within the input are summed into one component. It also explains the downstream effect that the saved meal can be re-logged as a whole, which is not derivable from annotations. It does not mention whether reusing an existing meal name fails or overwrites.

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 opening clause states the purpose immediately, followed by input mechanics and the downstream benefit. Every sentence carries information; the German parenthetical is a nice disambiguation cue rather than filler. Slightly dense but effectively front-loaded.

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 no output schema, the description should say what the call returns (a meal id or the created meal) so the agent can chain into joiva_log_meal. It also omits the failure behavior for a duplicate name even though the schema notes names are unique per user. Otherwise it covers the input model well.

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%, so the baseline is 3, but the description earns more by clarifying semantics the schema does not encode: that entryIds and components are mutually exclusive alternatives, that entryIds must reference already-logged entries, and that duplicates are aggregated. The one gap is that it does not say what happens if both are supplied or if neither is.

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 gives a specific verb and resource: saving logged foods as a named, reusable meal (recipe), with a concrete example ('merk dir das als Power-Bowl'). It implicitly separates itself from joiva_log_meal ('can then be logged again as a whole') but never names a sibling or states explicitly how it differs from joiva_list_meals or joiva_share_meal.

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 context is implied: use this when you want a reusable meal built either from already-logged entries or from explicit food/gram pairs. There is no explicit statement of when not to use it, no prerequisites (e.g. entries must exist in today's log), and no named alternative such as joiva_log_meal versus joiva_plan_food.

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