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

With no annotations, description must disclose behavioral traits. It reveals the tool uses Black-Scholes for European options and binomial for American, and notes it's paid-tier only. This provides useful model-specific context, though it doesn't detail error handling or data sources.

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 sentences, zero wasted words. All information is essential and front-loaded: action, resource, models, and constraint (paid tier). Highly efficient.

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?

No output schema means description should clarify return values, but it only states what is calculated, not what the agent receives (e.g., object structure, aggregation). The schema's 'description' field for options covers per-option and portfolio results, partially compensating. Still, the description leaves a gap.

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 100%—all parameters are described in the schema. The description does not add new semantics beyond stating the tool calculates Greeks per option or portfolio, which is already implied by the tool name and schema. 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?

Description clearly states the tool calculates option Greeks (delta, gamma, theta, vega, rho) for individual options or portfolios, using specific models (Black-Scholes, binomial). This directly conveys the resource and action, distinguishing it from broader risk tools like 'analyze_risk'.

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?

No guidance on when to use vs. sibling tools. The description lacks explicit context for appropriate usage, such as prerequisites or conditions for choosing this over alternatives like 'analyze_risk' or 'monte_carlo_simulation'.

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