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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, so the safety profile is covered. The description adds genuinely new context beyond that: US medians come from the Federal Reserve while other countries are labeled estimates, which matters for how an agent should present confidence in the numbers. It does not describe pagination or result shape, but neither appears to apply.

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 content is front-loaded in the first sentence, then age semantics, then usage examples, then provenance — a sensible ordering with no filler. It is dense but every clause carries information an agent needs; only the long comma-separated first sentence is slightly heavy.

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 carries the burden of describing returns, and it does so by naming the three statistics returned per age group. The only residual gap is that it does not indicate which countries are supported, though list_supported_countries exists as a sibling for that.

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 baseline is 3, but the description adds real meaning to the age parameter: it spells out the group bins (under 35, 35 to 44 … 75 or older) and explains that passing an age singles out the group it falls into. That resolves the ambiguity of how a continuous age maps to a bucketed result, which the schema only gestures at.

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 a specific resource and scope: household net worth by age of household head, returning median plus top 10% and top 1% cutoffs per age band. It also enumerates the age bands, so an agent knows exactly what the returned rows represent. It stops short of naming sibling tools like country_net_worth_thresholds or net_worth_percentile to distinguish the dimensions, which keeps it from 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?

It gives three concrete natural-language query examples ('average net worth at 30', 'top 1% net worth at 40 in the US', 'median net worth by age in Germany'), which effectively tells the agent when this tool is the right pick. It does not state exclusions or point to the sibling tools for threshold- or percentile-shaped queries, so the routing guidance is implicit rather than explicit.

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