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

Annotations already declare readOnly/idempotent/openWorld=false, but the description adds real method context: every lever and the baseline run 3,000 simulated years on the same seed, so differences come from the lever, not luck. It also notes the computation is pure arithmetic with nothing stored. It stops short of flagging cost/runtime for ~30,000 simulated years, but the disclosure is well beyond the annotations.

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?

Front-loaded with the core action and ranking criterion, with no filler. The long lever enumeration earns its place because it defines the exact scope of what is tested, and the methodology rationale is compressed into two tight sentences.

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?

No output schema exists, so the description carries the return-value burden, and it does describe what is produced (a ranking of levers by shortfall probability with a money tiebreak). It lacks detail on the result's shape or the baseline row, but for a 24-parameter, zero-required tool it is otherwise complete.

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% with 24 fully documented parameters, so the schema does the heavy lifting and a 3 is the baseline. The description only adds a framing sentence ('a preset plus any overridden inputs'), which is a minor structural hint rather than new meaning about individual fields.

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 precise verb+resource ('Test nine single changes ... and rank them') plus the exact ranking metric (lowering the chance of running short over 52 weeks) and tiebreak (change in year-end money). It enumerates all nine levers and explicitly frames itself against the sibling simulation ('Takes the same business description as a cash year simulation'), so it is distinguishable from simulate_cash_year without opening any schema.

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?

It establishes clear usage context by tying itself to the cash-year simulation inputs, implying it is the comparison counterpart to that tool. However, it never explicitly names simulate_cash_year or states when to prefer a single simulation over the lever ranking, so the agent must infer the routing.

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