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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds real context beyond that: it discloses the returned payload (g, oz, lb, kg, USDA sample range, weight lost, and the USDA row used), which is valuable given there is no output schema. It does not cover failure behavior for unmatched cuts or the precision/rounding of results.

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 sentences, front-loaded with the core transformation and data source, followed by a return-value sentence that earns its place because no output schema exists. Dense but not padded; the lean-ratio note is the only slightly tacked-on clause.

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 5-parameter, read-only, no-output-schema tool, the description covers the transformation, source data, discretization of food/method, and the full return shape. The remaining gap is edge-case behavior (unknown cut or method, out-of-range handling) and how to chain to find_cooking_yield when yields are missing.

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%, including examples for food and method, so the baseline is 3. The description adds the notable semantic that food accepts ground-beef lean ratios like 80/20 or 93% lean, but otherwise restates what the schema already documents (yield_id overriding food and method is already in the schema).

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 names a specific transformation (raw weight -> cooked weight) with a concrete data source (USDA Table of Cooking Yields) and domain scope (meat and poultry, including ground-beef lean ratios). It is clearly distinguishable from find_cooking_yield/list_cooking_yields because it is the conversion step, but it never names the reverse sibling convert_cooked_to_raw, so an agent must infer the direction split from the name alone.

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 is implied rather than stated: an agent can infer 'call this when you have a raw weight and want cooked weight', and the yield_id note points at find_cooking_yield/list_cooking_yields as upstream sources. There is no explicit when-not guidance (e.g. use convert_cooked_to_raw for the inverse) and no statement of what happens for an unrecognized food or method.

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