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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and closed-world behavior. The description adds a clear error contract: invalid input returns an {"error": ...} object rather than raising a protocol error, and it notes that retrying after correction is safe.

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 core purpose is front-loaded, followed by a concise example, usage guidance, and error behavior. Despite covering several points, every sentence contributes useful information for correct invocation.

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 tool is simple, has an output schema, and the description still covers purpose, inverse relationship to a sibling, example input/output, usage exclusions, and error semantics. Nothing material is missing for an agent to call it correctly.

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%, so parameter definitions already carry the baseline. The description still adds value by showing the semantic relationship through a concrete example: net_target 100 with 2.9% and $0.30 fees returns charge 103.4, fee 3.4, net 100.0.

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 computation in concrete terms: compute gross charge from a target net after percentage and fixed fees. It also distinguishes itself explicitly as the inverse of processor_fees, so an agent can tell it apart from sibling calculation tools.

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?

Gives explicit when-to-use guidance ('Use when the payout is the fixed requirement') and when-not-to-use guidance ('Not when the price is already set'), and names processor_fees as the inverse alternative.

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