Forecast total cost / budget (Monte Carlo)

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

Annotations already establish readOnly/idempotent/closed-world safety, and the description adds real behavioral value: it discloses the percentiles returned, the distribution shape output, and the conditional behavior when `budget` is supplied. It stops short of discussing iteration cost or runtime, but the safety profile is well covered.

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?

Three sentences, each earning its place: what it does, what it returns, and when to prefer it. Purpose is front-loaded before the outputs and the use-case note.

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 complex simulation tool with one required parameter, a full schema, and an output schema, the description supplies everything an agent needs to decide and invoke correctly; return-value detail is properly left to the output schema.

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 baseline is 3, but the description goes beyond it by explaining the semantic intent of the optimistic/most-likely/pessimistic triple (a three-point estimate summed into a total) and the meaning of the optional budget cap. Reproducibility of the seed is left to 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?

States a specific verb and resource ('Run a Monte Carlo simulation over a list of cost line items... probabilistic forecast of the TOTAL budget') and enumerates the outputs (P50/P80/P90/P95, mean, stdev, distribution shape). This clearly separates it from the sibling forecast_duration/forecast_completion tools, which forecast other quantities.

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?

Gives a clear use context ('Ideal for building a contingency-aware estimate instead of a single point number') and explains the optional `budget` use case, but never references siblings like pert_estimate or sensitivity_analysis, so no explicit when-not guidance.

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