Get vegetable yield percentage

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), so the description's job is to add data context — and it does: it discloses the data source and vintage (USDA SR28 refuse data) and precisely what the returned figures represent, including the definition of edible yield. It omits behavior for an unmatched or ambiguous food name, which is the main residual gap.

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 dense sentence that front-loads the primary value (edible yield percent) and then adds secondary outputs in descending importance. Every clause carries distinct information — parenthetical definitions, refuse details, household weights, source — with no repetition of the title or annotations.

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 must carry the return-value burden, and it does so thoroughly by naming each returned figure. For a one-parameter read-only lookup this is nearly complete; only the failure mode for unrecognized foods is unaddressed.

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 itself supplies format guidance and five example values, so the schema does the heavy lifting. The description reinforces the 'raw' constraint on the input, but adds no matching or normalization rules beyond what the schema already says. Baseline 3 is appropriate for a single fully documented parameter.

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 states a specific resource (USDA edible yield percent for a raw vegetable/fruit) and enumerates the exact outputs: refuse percent, refuse description, household weights, and as-purchased weight. It is far more specific than the title alone. It does not, however, distinguish itself from siblings such as calculate_edible_weight or list_vegetable_yields, leaving an agent to infer which of the three yield-related tools to call.

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 explicit when-to-use or when-not-to-use guidance, and no sibling is named. The closest thing to guidance is the implicit framing that this is a per-food reference lookup rather than a calculation, but that distinction from calculate_edible_weight is never stated. An agent must guess between four closely related tools.

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