finance_forecast_interpretation

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

With no annotations provided, the description carries full burden. It mentions routing through a domain-agent dispatcher under JWT/tenant/company scope, which adds some transparency about authorization. However, it does not disclose whether the tool is read-only or mutating, what side effects occur, or what the output contains. Despite an output schema existing, the description ignores it, leaving behavior opaque.

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 bullet list). It front-loads the key action phrase and then provides parameter details. There is no extraneous information, but it could be better organized with clear sections. Overall, it is appropriately sized given the minimal content.

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?

Given the existence of an output schema, the description should explain the return format or purpose of the output, but it does not. The tool has many finance siblings, yet the description offers no differentiation. The parameter descriptions are minimal. The description is incomplete for the tool's apparent complexity and context.

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?

While schema description coverage is 0%, the description adds interpretations: message is a 'Free-text objective' and inputs are 'Optional JSON string of structured inputs'. This adds some meaning beyond the raw schema. However, the descriptions are generic and lack specifics on the objective's expected format or the structure of the inputs, so the added value is moderate.

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 tautologically states 'Run the finance domain agent action' without explaining what the action does. It does not clarify that the tool interprets forecast results or generates interpretations, leaving the purpose vague. The name suggests interpretation, but the description adds no specificity, and siblings like finance_forecasting and finance_forecast_sensitivity are not distinguished.

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 alternative finance tools or other tools. There is no mention of prerequisites, context, or exclusions. The agent is left to guess if this tool is appropriate for interpreting forecasts or performing other actions.

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