wealth_advisory_wealth_monte_carlo_retirement

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

Annotations already signal readOnlyHint=false and destructiveHint=true, so the description adds no new behavioral context. It does not disclose what gets modified, whether results are persisted, what side effects occur, or how the action is destructive. Mentioning JWT, tenant, and company scope is authentication context, not behavioral transparency.

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 description is short, front-loaded with the primary action, and uses a clear Args section. Every line adds some information, and there is no redundant filler. It could be improved with domain-specific details, but as a concise pass-through wrapper it is well structured.

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?

Even though an output schema exists, the description is too generic to be complete for this specific tool. An agent needs to understand what a Monte Carlo retirement simulation entails, what inputs are relevant, and how to formulate a meaningful message. The current text only documents that it routes to a dispatcher, leaving the domain-specific usage entirely unaddressed.

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 0%, so the description must compensate. It only adds generic labels: message is a 'free-text objective' and inputs is an 'optional JSON string of structured inputs.' It does not explain what objective format is expected or what keys/values the structured inputs JSON should contain for this specific Monte Carlo retirement action.

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 states that it runs the wealth_advisory domain agent action `wealth_monte_carlo_retirement`, giving a clear verb and resource. However, it never explains what Monte Carlo retirement actually does or what outcome the agent should expect. The tool name hints at retirement simulation, but the description itself does not differentiate it from sibling wealth_advisory actions like `wealth_advisory_wealth_retirement_withdrawal`.

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?

There is no guidance on when to use this tool versus alternatives. It only describes routing mechanics through the domain-agent dispatcher and scoping under JWT, tenant, and company. The agent cannot determine whether this tool is appropriate for a given retirement-planning task versus running `wealth_advisory_chat` or another wealth action.

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