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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds meaningful context beyond annotations: the data source (LiveDataLink historical volatility series 2019-2024), the derivation nature of the results, and the specific computed metrics. It does not contradict annotations, and the 'not investment advice' caveat adds appropriate framing.

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 compact given the analytical complexity, front-loading the verb and resource before enumerating outputs. The list of metrics is long but each item earns its place by clarifying exactly what the tool returns. The final disclaimers are short and non-redundant.

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?

There is no output schema, so the description carries the burden of indicating what results to expect; its metric list largely covers that. It also identifies the data source, ticker scope, and lookback behavior. It is not fully exhaustive regarding return shape or edge-case coverage, but it is sufficient for an agent to select and invoke the tool 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?

Schema description coverage is 100%, so the baseline is 3 and the description does not need to compensate. The description references the lookback window indirectly through the metric definitions but does not repeat or extend the schema-level documentation for ticker, as_of, or lookback_days. It adds no param detail beyond the schema.

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 opens with a specific verb ('Compute'), a clear resource ('derived options-volatility analytics'), and a target scope ('US ticker'). It enumerates concrete outputs (IV Rank, IV Percentile, Variance Risk Premium, 52-week IV high/low, IV momentum), which sharply distinguishes it from raw-history siblings like options_history_volhist.

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 implies when to use the tool: when derived volatility analytics rather than raw historical series are needed, framing itself as 'Derived synthesis over the options-history store.' However, it does not explicitly name alternative tools or state conditions under which a caller should prefer a sibling such as options_history_volhist or options_chain.

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