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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds genuinely non-obvious behavioral context: these are asking prices, not closed transaction prices, which materially affects interpretation of the medians. It does not disclose sample-size thresholds, data recency, or geographic coverage, so not a 5.

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 output metrics are front-loaded in the first clause, followed by grouping dimensions and realistic question examples. Three compact sentences with no filler, though the metric enumeration is dense and could be trimmed without loss.

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 effectively serves as the return-value spec by listing the aggregates (median, p25–p75, gastos comunes, total, price per m², accessibility/cost rankings). The asking-price caveat is included. Missing is any statement of data recency, temporal window, or whether coverage is national or Montevideo-only, which matters for an openWorldHint aggregation tool.

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 every parameter is already documented in the schema (type default 'los dos', bedrooms 0 = monoambiente, currency default UYU, tildes required for department, neighborhood requires department). The description's 'por departamento, barrio, tipo y dormitorios' mirrors the schema rather than adding new semantics, and currency is not addressed in prose. Baseline 3 applies.

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 the resource (rental market) and enumerates the exact statistics returned: median, p25–p75 range, gastos comunes, monthly total, price per m², plus cheapest/priciest neighborhoods. The closing note 'Son precios pedidos' (asking prices) further sharpens what this measures, separating it in spirit from estimate_fair_rent. It stops short of naming a sibling tool explicitly, so a 4 rather than 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?

Two concrete user-question examples ('¿cuánto sale un 2 dormitorios en Pocitos?', '¿dónde me alcanza con $30.000?') give clear positive usage triggers and map directly onto the bedrooms/neighborhood parameters. No explicit when-not conditions or named alternative tools are given, which keeps this out of 5 territory.

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