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

Annotations already cover read-only/idempotent/non-destructive safety, and the description adds substantial extra behavior: it warns that exactly one method must be supplied with its declared inputs (no defaults) and that unknown methods, missing inputs, or extra fields yield an INVALID_ARGUMENT error envelope rather than raising. This is genuinely useful call-time behavior not derivable from annotations.

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?

Front-loads purpose, then method-to-input mapping, then error semantics. The method list is dense and long but each entry carries required information; some parenthetical metric glosses could be trimmed without loss.

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 34-param, one-required-field dispatcher with an output schema, the description covers everything the agent needs: method enumeration, per-method required inputs, single-method constraint, and error behavior. Return-value detail is correctly left to the output schema.

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?

Although schema coverage is 100%, the description supplies the critical cross-parameter mapping the schema cannot express: which inputs each method value requires (e.g. ltv needs arpu/gross_margin/churn_rate; nvt needs market_cap/transaction_volume). The schema itself defers to the description for this ('the tool description lists the exact inputs each value requires').

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 verb+resource ('compute the metrics that anchor valuation') and enumerates the concrete industry domains and metrics covered (ARR, NRR, take rate, NVT, etc.). It explicitly differentiates from siblings by declaring it returns operating metrics, not a valuation.

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?

Clearly routes the agent: the outputs are 'inputs to calculate_market_multiple or calculate_dcf,' which distinguishes this tool from the valuation siblings. It does not give explicit exclusion criteria for individual methods, but the when-to-use context is clear.

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