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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds real value beyond that by disclosing that the tool is free, that the APR is simple (not compounded), and that inputs are assumptions rather than live data. It says nothing about what the calculation returns or how fees and losses are applied, which is the main behavioral 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?

Two short sentences with no filler, and the core action is front-loaded before the caveat. Efficient, though the second sentence is a disclaimer rather than substantive guidance.

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 and six nested numeric parameters, the description should say what the calculation produces (net return, effective APR, loss-adjusted result) and how the two loss percentages interact. It covers the conceptual framing but leaves the agent guessing about the result shape and the meaning of several inputs.

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 0%, so the description must carry the parameter burden, and it only partially does: it signals that fees and loss scenarios are inputs, loosely mapping to entry_exit_fees_usd, principal_loss_percent and reward_price_drop_percent. It never explains apr_percent versus days, the 3650-day cap, or what reward_price_drop_percent applies to given no reward-amount parameter exists.

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 and resource: 'Calculate simple-APR returns after supplied fees and loss scenarios.' That is far more precise than the tool name alone and clearly separates it from the quote/payment/risk siblings. It stops short of naming a sibling or stating scope boundaries explicitly, so it is not a 5.

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?

The line 'Inputs are assumptions, not live quotes or recommendations' implicitly steers the agent away from quote tools toward this one for hypothetical modeling, which is useful routing. However, there is no explicit when-to-use or when-not-to-use statement, and no mention of prerequisites or alternatives by name.

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