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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds meaningful context by specifying that it compares multiple published assumption sets and returns success rate and median outcome as sensitivity metrics, which is beyond what annotations provide. No contradiction exists.

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?

A single well-structured sentence states the core behavior, the output metrics, and the purpose (sensitivity analysis). Every clause earns its place and there is no redundant or filler 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 14-parameter tool with no output schema, the description supplies essential output expectations (success rate and median outcome under each set) while the schema covers all parameter semantics. The open-world/read-only annotations and the sibling list_return_assumption_sources provide enough surrounding context for correct invocation.

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 the schema fully documents all 14 parameters and their defaults. The main description adds no parameter-level detail beyond the schema. The presence of both a singular 'returns_source' and a plural 'sources' array could be mildly confusing, but the schema descriptions clarify each.

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 uses a specific verb and resource: it 'runs the same plan against several published capital market assumption sets' and returns success rate and median outcome under each. This clearly distinguishes it from the sibling run_retirement_projection (single plan, single forecast) and list_return_assumption_sources (listing sources).

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 implies the use case—comparing how different return forecasts affect a retirement plan—and the wording makes it distinct from a single projection. However, it does not explicitly state when to use this tool versus run_retirement_projection, nor does it mention any exclusions or prerequisites.

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