Amazon profit and margin (FBA or FBM)

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds genuinely new behavioral context: strict input validation that rejects invalid or unknown arguments with a message naming the field and never silently adjusts, plus disclosure that it shares the fee engine with shoptrueprofit.com calculators and returns assumptions and a fee-table version/date. This is exactly the kind of beyond-annotation detail the dimension rewards.

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 sentences, each doing work: purpose and inputs first, then what is returned, then validation behavior. The middle sentences are dense but front-loaded and free of filler; only the fee-engine branding sentence is near-optional.

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 18-parameter, four-enum, conditionally-branched FBA/FBM calculator with an output schema present, the description covers the split between fulfillment modes, the conditional input requirements, the date-driven rate effects, and the return contents and validation contract. An agent has everything needed to call it correctly without reading the schema end to end.

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 the schema already documents all 18 parameters thoroughly, including conditional 'FBA (required)' markers. The description restates the input groups (price, category, item cost, inbound vs label cost, ad spend) but adds no syntax, format, or conditional logic the schema does not already carry, so the baseline 3 is appropriate.

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 profit, margin and break-even price for one unit sold on Amazon.com US) and enumerates the cost inputs, so the agent knows exactly what the tool produces. It does not explicitly differentiate itself from siblings like amazon_fees or amazon_target_price, and its promise of a 'break-even price' actually overlaps the apparent territory of amazon_target_price, which leaves a small selection ambiguity.

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 description gives conditional context (FBA requires package dimensions and weight; FBM uses label cost; inbound cost is FBA-only; ship_date drives peak/surcharge/storage), which implies usage. But it never says when to prefer this tool over amazon_fees or amazon_target_price, and no exclusions are stated, so the routing decision is left to inference.

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