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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world). The description goes beyond them with genuinely useful traits: deterministic seeded Monte Carlo, sampling imposed on user-supplied distributions, the refusal of affine units, and CPU/direct-call execution with no planner binding. Determinism and the input-conditioning caveat are exactly the behavioral facts an agent needs.

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 tight sentences with the core comparison front-loaded and no filler. The telegraphic phrasing ("CPU, direct-only; no planner binding") is dense but each clause carries distinct information.

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?

With an output schema present, return values needn't be detailed, and the description still previews the budget/interval/finding outputs. Combined with 86% schema coverage and full annotations, the definition is complete enough for correct invocation, though the description could say more about how the two methods are reconciled when they disagree.

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 description coverage is 86%, so the schema already documents seed, samples, coverage, units, expression grammar and correlations. The description adds only a little beyond it (1–16 input bound, no affine units), so baseline 3 is appropriate.

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 specific operations (dimension check, first-order GUM vs seeded Monte Carlo comparison) on a specific resource (an explicit model of 1–16 inputs) and names what is returned (uncertainty budgets, coverage intervals, convergence/linearization findings). No sibling tool occupies this uncertainty-propagation niche, so the agent can select it unambiguously.

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?

"Conditional on supplied distributions; no affine units" and "CPU, direct-only; no planner binding" give clear applicability conditions and clearly exclude the planner/route siblings. It stops short of naming an explicit alternative or stating when NOT to use it, so it is strong context rather than full routing guidance.

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