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

Annotations already declare a safe, read-only, idempotent, closed-world operation, so the safety profile needs no restating. The description adds the return categories (hydration % and dough type firm/standard/wet), which is useful, but the thresholds defining those categories are left unstated and the output schema already carries the return shape.

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?

Three compact sentences with the formula and purpose front-loaded, then inputs and outputs. Every sentence is short and functional; the trailing list_bundles pointer is the only slightly tangential element.

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?

The output schema covers return values, so the description needn't explain them in depth. Purpose, inputs, and outputs are all addressed; only the category thresholds for the dough type are missing, which is a minor gap for a simple two-parameter calculator.

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 both parameters (flour_grams, water_grams) are already fully documented in the schema. The description's 'Inputs: flour g, water g' merely restates that, adding no syntax or unit nuance beyond the structured data. Baseline 3 applies.

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 ('Compute'), the exact resource (baker's hydration %), and even the formula (water/flour×100), which unambiguously identifies the tool and differentiates it from generic calculators like calculate_hydration (water intake). An agent can select it without opening the schema.

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?

Says 'Use for bread recipe analysis,' which implies context but gives no explicit when-not conditions or named alternatives. The pointer to list_bundles for related 'cuisine' calculators is vague routing rather than a concrete alternative selection rule, and it does not distinguish itself from the similarly named calculate_hydration sibling.

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