part-d-cap

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

With no annotations at all, the description carries the full disclosure burden and meets it: it reveals fallback behavior (fails closed to 2026 for unsupported years, never extrapolates), clarifies a likely misconception (the MPPP spreads the SAME total without reducing it), and discloses the simulation's hard limits (plan prices and cost sharing are not held or inferred). These are exactly the behavioral traits an agent needs before invoking a financial simulation.

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 with every one earning its place: the computation summary, the year-scope/fallback rule, and the limitation disclaimer. The core functions are front-loaded in the first sentence, and there is no filler or repetition of schema 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?

For a five-parameter simulation with no output schema and no annotations, the description covers scope, supported years, fallback, limitations, and every output facet (projection, cap month, savings, MPPP comparison). The only real gap is return format — an agent knows what will be computed but not the shape of the result — which prevents a 5.

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 100%, so every parameter is already documented in the input schema; baseline 3 applies. The description adds only modest param-level context — 'standard-benefit simulation' frames what monthly represents, and the fail-closed statement clarifies behavior for unsupported year values — but this is mostly behavioral rather than semantic. It doesn't materially change how any parameter should be filled in.

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 opens with specific verbs and resourcs: projects month-by-month Part D out-of-pocket spend against the statutory annual cap, identifies the cap-reach month, quantifies cap savings, and compares payment timing against the Medicare Prescription Payment Plan. It goes well beyond the tool name by defining the exact computation scope and by explicitly bounding what it is not (a plan-specific pharmacy quote).

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 when-to-use context is clear — any need for a standard-benefit cap projection or an MPPP timing comparison. It also states an explicit exclusion, 'NOT a plan-specific pharmacy quote,' which tells an agent to avoid it when negotiated prices or plan cost sharing are at play. It doesn't name alternative tools, but with no siblings that exclusion is the best available guidance.

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