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

Annotations already declare readOnlyHint/openWorldHint=false/destructiveHint=false, but the description adds genuine behavior: contributions are level and end-of-period unless paymentTiming is "begin", the rate is a fixed assumption rather than a forecast, and an unrepresentable result is an error. It does lose some points because the "Edge cases" run largely restates numeric bounds the schema already declares, and nothing is said about outcome magnitude or when an error is returned.

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?

It is front-loaded: definition, rate convention, timing convention, exclusions, examples, then return fields. However, the fraction notation is stated twice (0.07 = 7% then 0.05 is 5%) and the long "Edge cases" block duplicates schema bounds nearly verbatim, so it is denser than it needs to be.

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?

There is no output schema, and the description compensates by enumerating the returned fields (futureValue, fvOfPayments, interestEarned, ratePerPeriod, periods, etc.). Combined with the assumption disclosure and edge cases, an agent has everything needed to call this correctly for a 6-parameter tool.

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; the description earns above baseline by explaining the nominal-rate convention (rate per period = annualRate / periodsPerYear) and the coupling constraint that years x periodsPerYear must be whole when a payment is present. Those are semantic rules an agent could not infer from the individual property descriptions alone.

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?

"Future value of a starting sum, regular contributions, or both, grown at a fixed rate" gives a specific verb+resource plus the exact scope (lump sum, annuity, or both). It distinguishes itself from the nearest sibling by naming workflow.run_monte_carlo for outcome ranges, so an agent can route without opening a 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 supplies concrete trigger utterances ("what will $10,000 plus $500 a month be worth in 30 years at 7%?") and an explicit alternative for a different need (run_monte_carlo for a range of outcomes). The "Not covered" sentence enumerates the cases that should be rejected or routed elsewhere: time-varying rates, uneven/growing contributions, inflation, taxes and fees.

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