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

The annotation declares readOnlyHint=true, establishing a safe read operation. The description adds behavioral context by specifying 'Live' data, 'per expiry' structure, and the Alpha tier access requirement, going beyond the annotation without contradicting it.

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?

The description is three sentences, front-loaded with the core output definition, followed by use cases and access note. Every sentence provides meaningful information with no redundancy or fluff.

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?

Despite having no output schema, the description enumerates exactly what the tool returns (SVI parameters, ATM variance, ATM IV) and notes the 'per expiry' structure. Combined with the simple two-parameter schema, this is sufficient for an agent to invoke the tool and interpret results correctly.

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?

The input schema has full 100% description coverage for both parameters (apiKey and symbol). The description does not add parameter-specific details beyond the schema; it focuses on output and use cases, so it adds no extra semantics beyond the baseline.

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 clearly states the tool provides a live SVI-fitted volatility surface per expiry, listing the exact calibrated parameters (a, b, rho, m, sigma) plus ATM total variance and ATM IV. This distinguishes it from sibling tools like get_surface, which likely return raw surface data rather than SVI model parameters.

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 explicit use cases: surface reconstruction, SVI arbitrage checking, variance swap pricing, and quant vol-model inputs. It also notes Alpha tier requirement, which is a clear prerequisite, though it does not explicitly mention alternatives or when not to use it.

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