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

Annotations only declare readOnlyHint and openWorldHint; the description adds substantive behavior beyond that: missing prices and IVs are backfilled from current market data, probability is computed at the earliest expiry using a lognormal model on 30-day implied volatility, and calculatorUrl opens the position on an external site. It stops short of covering failure modes or rate limits, but the model assumptions are unusually well disclosed.

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?

Four dense sentences, front-loaded with what is calculated and for what instrument, followed by input defaults, model assumptions, and the calculatorUrl return behavior. No sentence is redundant and nothing important is buried.

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 multi-leg options calculation with no output schema, the description covers the returned metrics, the calculation model, the expiry used, input backfilling, and the external URL behavior. Combined with read-only annotations, an agent has enough to call it correctly without further documentation.

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 75%, so the schema already documents most fields, but the description adds meaning the schema does not: the cap of 8 option legs plus 1 stock leg, the fact that omitted price and IV values are auto-filled from market data, and that probability is evaluated at the earliest expiry. This meaningfully reduces ambiguity about how partial inputs are treated.

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 a specific calculation (probability of profit, breakevens, max profit and max loss) for a specific resource (an options position) and names the external engine that performs it. It also states the leg composition limit, making the tool's scope immediately distinguishable from generic siblings like calculate_position.

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?

Usage is implied by the leg-composition constraint and the note that omitted prices and IVs are filled from market data, which tells an agent it can call with sparse inputs. However, it never says when to prefer this over calculate_position or how it relates to find_options, get_expirations, or get_option_chain, so the agent must infer routing.

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