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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: the flow count is defined as the never-reduced cohort, and the live-stock series starts 2026-09-05 and is forward-only, which materially affects how results should be interpreted. It stops short of noting rate limits, pagination, or latency.

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 first sentence front-loads the core value proposition and the metrics returned, and the second carries the interpretive caveats. Dense but every clause carries information; the metric enumeration is long yet earns its place by describing output scope.

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?

An output schema exists, so return values need not be explained, and annotations cover the safety profile. The metric list and the data-definition caveats make it usable, but the complete absence of per-parameter meaning plus no routing to sibling tools leaves real gaps for an agent choosing and configuring this call.

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% across five parameters, so the schema contributes no semantics and the description must compensate. Beyond loosely implying an area and a monthly window, it says nothing about area_code vs area_type interaction, channel values, or what the bedroom_band enum means for the aggregates, leaving most parameters undocumented in both places.

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?

It states a specific resource (supply and demand for an area) and enumerates the concrete outputs: live stock count, median days on market, new-home count, listings added/reduced, reduction share, agent concentration, asking-to-sold, days to completion. That is far more specific than a tautology. It does not, however, name or rule out the closest siblings such as area_stock_profile, listing_stock_series, or area_report, so an agent must infer the boundary itself.

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 scoping constraints ('UK only. Free.') and implies the use case by framing the tool as a combined one-call supply+demand view, which suggests using it instead of stitching together stock and flow tools. It never states explicitly when to prefer it over the sibling area/stock/index tools, so usage is implied rather than directed.

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