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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds real behavioral value beyond that: unpublished measures are returned as null with the reason, never zero, and there is no cohort HPI (only whole-area, explicitly labelled). That null-vs-zero contract is exactly the kind of disclosure that prevents misreading results.

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 bulk of this single run-on sentence enumerates return fields — indexes, agent concentration, days to completion, SearchQuery links — which an output schema already provides, so many tokens do not earn their place. The input-relevant facts (window default, id sourcing, null semantics) are buried mid-stream rather than front-loaded.

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 an output schema is present, the description need not restate returns, yet it ensures the agent understands the result contract (nulls with reason, no cohort HPI, index coverage) plus how to obtain the required id. Nothing an agent needs to call this correctly is missing.

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 carries the full burden — and it largely meets it: `window` is defined as the number of months the series is sliced to (default 60), and `profile_id` is sourced from search_entities with entity market_profiles. Neither parameter is left to guesswork, though no format or validity constraints are given.

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 — a single market profile for an area × bedroom cohort — and enumerates the categories of measures it returns, so the purpose is unambiguous. However, it never names or contrasts itself against close siblings such as area_report, market_facts, or market_yields, leaving the agent to infer differentiation.

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 provides one genuinely useful usage fact: profile_id comes from `search_entities` with entity `market_profiles`, and it notes the call is 'Free'. But there is no guidance on when to choose this over the many related market siblings, nor any exclusion criteria.

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