quant_models

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, which convey safety and idempotency. The description adds that models are 'pre-computed' and supports quarterly and date range parameters. It doesn't contradict annotations. However, it omits details like auth requirements, rate limits, or how multiple tickers are handled in output.

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 brief (two sentences plus a list) and front-loads the key purpose and required parameter. The list of indicators is useful but could be more integrated. Overall, it is concise with little waste, though the list length could be trimmed by referring to the schema.

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 21 parameters and an output schema, the description covers essential inputs (tickers, quarterly, dates) but ignores many optional parameters (e.g., growth, lag, trailing, WACC). Given the tool's complexity, the description could provide more guidance on which parameters apply to which models. Still, the output schema exists, and schema covers all params, so the description is adequate but not thorough.

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 the schema already documents every parameter. The description adds minimal extra semantics: it highlights the required 'tickers' parameter and the 'quarterly' and date parameters. The list of indicators in the description is redundant with the schema enum. Thus, the description adds value only modestly 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 clearly states the tool provides pre-computed financial models like WACC, DuPont, Altman Z-Score, etc. It names specific models and distinguishes itself from sibling tools (e.g., market_data, ratios) via its focus on quantitative financial modeling. The required 'tickers' parameter and comma-separated format are also mentioned, giving a precise scope.

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 lists available indicators but does not explicitly state when to use this tool over siblings. It implies usage for financial model computation but lacks when-not-to-use guidance or alternatives. The instruction to use comma-separated tickers provides some usage context, but no exclusions or prerequisites are given.

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