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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety and purity are largely covered. The description does add genuinely useful context that annotations cannot express: no auth, no rate limits, 2-decimal rounding, and that unknown methods or missing method-required parameters return an error. It does not, however, contradict the annotations, so this sits at a solid 3 rather than the annotation-only baseline of 2.

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?

Dense but well front-loaded: purpose, alternatives, method-to-parameter mapping, then units, return shape, and error behavior. The single long paragraph is slightly heavy, but nearly every clause earns its place and no sentence is wasted.

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?

With an output schema present, the description need not re-explain return fields, and it still covers the error path, unit conventions, and full method-parameter mapping. This is complete for a 15-parameter, method-dispatched valuation tool, and the annotation layer covers safety.

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%, so per-parameter meanings are already documented. The description adds value beyond the schema by specifying which parameters each method consumes (e.g. lending needs loan_book + roe + pe_multiple), and clarifying the fraction convention and that all non-method parameters are optional with defaults where defined.

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 action ('value and size fintech business models') and enumerates the exact model families it covers (payment revenue, lending, payment-processor DCF, neobank). It also names the sibling it is not (valuation_saas) so the agent can route correctly without opening either schema.

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?

Gives both when-to-use ('payments, lending, and neobanks') and the explicit alternative for the adjacent case ('for SaaS-style unit economics use valuation_saas'). It further tells the agent how method selection drives the required inputs, removing the main invocation ambiguity.

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