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

Annotations already cover readOnly/idempotent/non-destructive/closed-world, so the bar is lower. The description adds real value by disclosing that the result is model-derived and rests on the lognormal distribution implied by options prices, which tells the agent the output is an assumption-based estimate rather than an observed frequency.

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?

A single front-loaded sentence that leads with the computed quantity and then qualifies it with the model assumptions. Dense but every clause contributes; no filler or restatement of the tool name.

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 pure four-parameter calculator with no output schema, the description conveys the computation, its inputs and its modeling assumption well enough to invoke correctly. The only gap is the shape of the return value (decimal vs percent), which is left implicit.

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 price, level, iv_pct and days. The description reinforces the interpretation of 'level' as a breakeven or short strike and ties IV to the lognormal model, but adds no units, ranges, or formatting beyond what the schema states.

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 computed quantity ('model probability that a stock finishes above or below a price level ... by a date') with the inputs that drive it (implied volatility, lognormal assumption). It is distinguishable from expected_move and profit_calculator by being a probability rather than a price move or P/L, though it never names those siblings explicitly.

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 phrase 'a breakeven or a short strike' hints at the options-trade context, but there is no explicit when-to-use statement and no routing against alternatives like expected_move or profit_calculator. The agent must infer the scenario on its own.

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