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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered externally. The description adds a genuinely useful behavioral trait beyond that: values are normalized per 100 g, which prevents misreading the returned panel as per-serving data. It omits auth needs, rate limits, and missing-food behavior.

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 short sentences, zero filler, and the core output contract (nutrient panel, per 100 g) is front-loaded before the input-sourcing hint. Nothing is redundant with the annotations or schema.

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?

An output schema exists, so return-shape explanation is not required, and the description still supplies the key unit convention plus the full input-acquisition path. Only edge cases (invalid food_id, missing data) are left unaddressed, which is acceptable for a single-parameter lookup.

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 schema already labels food_id as coming from search_foods, so baseline is 3. The description earns an extra point by widening the documented provenance to 'search_foods or lookup_barcode', adding meaning the schema alone does not convey.

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 ('Return the nutrient panel') with an explicit normalization basis ('per 100 g'), which tells the agent exactly what comes back. It names the sibling tools that supply the input (search_foods, lookup_barcode), which weakly differentiates it from the feeding lookups, but it does not contrast itself against calculation siblings like calculate_portion.

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 gives a clear prerequisite chain: obtain a food_id from search_foods or lookup_barcode, then call this tool. That is actionable context for when the tool is appropriate, though it stops short of any exclusions or a when-not-to-use clause.

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