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

Annotations already establish readOnlyHint and openWorldHint, lowering the burden. The description adds useful behavior beyond those annotations by specifying exactly what outputs are returned, including the notable detail that income assumptions are reported even when there are none. No contradiction with 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?

Two sentences with no filler. The purpose and the most decision-relevant output facts are front-loaded, and every clause contributes information about what the call does or returns.

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 no output schema, the description compensates by listing return fields and even an edge case (zero income assumptions). Required parameters and defaults are covered by the schema. It could add validation context such as age ordering or allocation-sum enforcement, but those are not required for a basic correct call.

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 schema already explains each of the 13 parameters and defaults. The description adds no parameter-level meaning except implying that income assumptions (pension, social_security, monthly_contribution) are reflected in the returned result. This meets the baseline but does not elevate it.

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?

Description opens with a specific verb ('Runs'), names the resource ('Monte Carlo retirement projection on the QuantCalc engine'), and lists concrete return artifacts (success rate, ending-portfolio distribution, assumptions). This makes the tool's function unmistakable and separates it from the sibling comparison and inspection tools.

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 description makes clear this is the tool for running a projection, so its primary use case is implied. However, it never says when to prefer a sibling like compare_return_assumptions or list_return_assumption_sources, or when not to use this tool. Guidance is implied rather than explicit.

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