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

The description goes well beyond the readOnly/idempotent annotations by disclosing that the total is a floor when 'complete' is false, that 'missing' names unpriced components, that a zero total is legitimate and potentially misleading, and that depositMonths is a stated assumption rather than a measurement. This gives the agent the mental model needed to interpret results safely.

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 dense but every sentence earns its place: it defines the resource, gives reading order, explains floor semantics, warns about zero totals, and clarifies the epistemic status of depositMonths. The key scoping statement is front-loaded before the caveats.

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?

Given the schema's strong parameter coverage, the read-only annotations, and the presence of an output schema, the description covers all critical calling and interpretation aspects: input components, output caveats, missing-data behavior, assumptions, and passport/destination edge cases. Nothing essential is left for the agent to guess.

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?

The input schema already covers 100% of parameters with useful descriptions, so the baseline is 3. The description adds important meta-semantics, especially that depositMonths is an assumption with no underlying global dataset, and that income is irrelevant to the arrival total. This extra context improves parameter understanding beyond the schema.

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 a specific resource and scope: the cash needed to arrive somewhere, itemized as entry fee, first month's rent, deposit, and verified long-stay visa fee. It explicitly contrasts this with ongoing monthly costs, which distinguishes it from related cost tools like compare_total_cost and estimate_micro_costs without requiring the agent to infer intent.

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 clearly frames when to use the tool ('to ARRIVE somewhere' versus 'what a month costs once you live there') and gives operational guidance like 'READ complete BEFORE totalUsd'. It does not explicitly name sibling tools to use for the monthly-cost case, so it stops short of a full when-not/alternatives statement.

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