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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds context by revealing the projection method ('daily-average linear projection'), which is useful, but it does not explicitly state whether the operation is read-only or if there are side effects, permissions, or limitations. It also does not describe the output format.

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 a single, coherent sentence that front-loads the core purpose and method. It contains no filler or redundant information, making it appropriately concise.

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?

For a tool with three well-documented parameters and no output schema, the description sufficiently explains the purpose and methodology. However, it lacks explicit guidance on when to use it versus siblings, and does not mention output expectations or edge cases (e.g., insufficient historical data). This leaves some gaps for an agent relying solely on the description.

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?

The input schema already provides descriptions for all three parameters (100% coverage), so the description does not need to add parameter details. The description does not add extra meaning beyond what the schema offers, maintaining the baseline score of 3.

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 a specific verb ('Forecast'), a resource ('future AI spend'), and a method ('daily-average linear projection'). It is readily distinguishable from sibling tools like budget_alert, cost_tracker, and model_breakdown.

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 implies when to use the tool (when a forecast of AI spend is needed based on historical usage), but it does not provide explicit exclusions or reference alternatives such as 'use budget_alert for budget monitoring'. The guidance is implied rather than stated.

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