forecast_azure_costs

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

With no annotations, the description explains the underlying mechanism (calls Microsoft's forecast endpoint, blends actual and forecast data). It does not disclose permissions, rate limits, or return format, but the behavioral description is adequate for a read-only forecast tool.

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 concise and well-structured: purpose first, then technical details, then parameter docstring, and examples. No wasted words.

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 2 optional parameters and no output schema, the description covers behavior, parameters, and example queries. It lacks output format details and potential error conditions, but overall is sufficient for an AI agent.

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 0%, but the description provides detailed parameter explanations: subscription_id meaning (all subs if None) and end_date format and default. This fully compensates for the lack of schema descriptions.

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 identifies the tool as forecasting Azure spend using Azure Cost Management's forecast model. It specifies the resource (Azure spend) and action (forecast), distinguishing it from generic forecast tools like 'forecast_costs'.

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 explains defaults and provides example queries, implying when to use (Azure-specific forecasting). It lacks explicit exclusion of alternatives, but the name and context suggest Azure-specific use.

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