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

Annotations already cover the safety profile (readOnlyHint true, destructiveHint false, openWorldHint false), and the description adds real modeling semantics on top: a fixed six-month/126-day horizon, payout events that reset the account to its starting balance, and that each payout follows the account's own rules. It does not discuss cost, rate limits, or determinism of the simulation, but the behavioral contract is substantially clarified.

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?

The scope ('for up to five accounts') and the output list are front-loaded, and every clause maps to something the tool returns or requires. The phrasing is dense and slightly awkward in places ('what one attempt is worth counting those payouts'), but there is no filler.

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, so the description carries the burden of describing return values, and it does so by naming each metric the agent will receive. Combined with the stated input modes and the six-month horizon, an agent has enough to call this correctly and interpret the result without further information.

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 a baseline of 3 applies, but the description adds meaning the schema cannot express: the two mutually exclusive input modes (a trades array paired with starting_balance, versus the four headline scalars win_rate, reward_to_risk, risk_per_trade, trades_per_day). That grouping is not stated in the schema and directly shapes how an agent assembles arguments.

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 names a specific verb+resource: it simulates, for up to five challenges, the chance of getting funded and the payout behavior of the funded account over its first 126 trading days. It enumerates the concrete outputs (average payouts, trader's share after split, time to first payout, account loss rate, expected value per attempt). It does not name which sibling to use instead, so it falls short of a 5.

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?

Usage is implied through the input modes ('Give trades with starting_balance, or the four headline numbers'), which tells the agent how to call it but not when to prefer it over test_stats, test_trades, or compare_challenges. There are no explicit when-not conditions or alternative routing.

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