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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds meaningful behavioral detail: the tool returns echoed debt_type/debt_type_label fields, has a not_representable error shape for extreme inputs, and is a calculation with a professional-verification caveat. No contradiction with annotations.

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 description is dense but well-structured: purpose first, scope, sibling routing, response shape, output modes, and error case. A few phrases restate schema details (e.g., output='summary' default), but every sentence earns its place and the critical scoping is front-loaded.

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 complex 14-parameter tool with no output schema, the description is notably complete: it covers the comparison's scope, when to use it, output variants, top-level response fields, and the not_representable failure mode. An agent has enough context to invoke it correctly without further inference.

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 each of the 14 parameters is already documented. The description adds contextual framing (post-payoff investing, tax implications, break-even) but does not explain any parameter beyond what the schema provides; it only slightly enriches output-parameter behavior (summary vs inline, not_representable).

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 the exact operation: 'Compares the guaranteed return of debt payoff against expected investment returns over a time horizon,' with a clear verb and resource. It also enumerates supported debt types and explicitly contrasts itself with calculate_opportunity_cost, making sibling differentiation immediate.

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?

Contains explicit when-to-use guidance: 'Pick this when the alternative to investing is paying down an existing debt balance; pick calculate_opportunity_cost when there is no debt.' It also gives output-selection guidance ('HEAVY tool: use output='summary' ... or output='inline'') and notes failure conditions with not_representable.

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