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

Annotations already cover the safety profile (readOnly, idempotent, closed-world, non-destructive), so the bar is lower. The description adds real value beyond them: it discloses data provenance (markets.json, 15-city sample), that YoY/vacancy/cap rate are the file's labeled estimates, that the 12-month illustration is FMR x CPI Shelter rate, that it is not a metro forecast, and that unknown cities error. That is substantive caveat and provenance context.

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?

Provenance is front-loaded, which is good, but the description is dense and drifts into tangential detail (the 12-month illustration and CPI Shelter rate) that reads as a run-on rather than tight scoping. Not wasteful enough to punish hard, but not crisp either.

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?

For a read-only lookup with annotations already carrying the safety profile and no output schema, the description does a fair job of explaining what is returned and where the data comes from. It remains incomplete on the three input parameters and on when to choose it over siblings, so it is adequate but with clear gaps.

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 only 33% (only slug is documented), so the description must compensate for city and state, and it does not. The only parameter-adjacent hint is 'An unknown city returns an error,' which weakly implies the city parameter but adds no format or semantics. The slug listing behavior lives in the schema, not the description.

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 specifies the resource concretely: city rows in markets.json (the 15-city sample), plus the sample median/mean those pages compute. An agent can tell what data comes back. It does not, however, differentiate itself from the sibling lookup_* tools (lookup_city_rules, lookup_hud_rent, lookup_rent_to_income), so it stops short of 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?

There is no explicit when-to-use guidance and no alternatives named, despite many sibling lookup tools. The only conditional behavior mentioned is 'An unknown city returns an error,' which is a behavior note, not usage routing. An agent gets no help deciding when this tool beats another.

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