finance_automl_forecast

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

No annotations are provided, so the description must disclose behavioral traits. It mentions scoping under JWT/tenant/company but does not state whether the tool is read-only or destructive, what side effects occur, or any prerequisites. The user is left guessing about the tool's impact.

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 relatively short and includes both the tool's purpose and parameter explanations in a few lines. It is not overly verbose, but some redundancy exists (e.g., repeating the tool name).

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?

The tool has an output schema, so return value details are not strictly required, but the description lacks a clear statement of what the tool produces (e.g., a forecast). It also omits context about when to use it or any prerequisites, leaving the agent underinformed.

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 the JSON schema itself has no descriptions (0% coverage), the description text includes explicit parameter documentation: 'message' is a 'Free-text objective for the action' and 'inputs' is an 'Optional JSON string of structured inputs.' This adds meaningful 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 essentially restates the tool name ('Run the finance domain agent action `finance_automl_forecast`') without specifying what the action actually does. It fails to clarify that this tool is for generating financial forecasts, which is implied by the name but not stated.

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?

No guidance is provided on when to use this tool versus alternatives. Among sibling tools are many finance-related tools like 'finance_forecasting', 'finance_forecast_interpretation', etc., but the description offers no differentiation or context for selection.

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