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

There are no annotations, so the description carries the transparency burden. It clearly scopes the response to exactly four weekly smart-median observations with change percentages, which sets baseline expectations. However, it does not disclose ordering, recency guarantees, missing-data behavior, or whether this is purely a read operation; those are left for the agent to infer.

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 description is one clean sentence, front-loads the core response ('last four weekly smart-median observations'), and uses every part to add information. There is no fluff, repetition, or irrelevant detail.

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 single-parameter data-lookup tool with an output schema available, the description is mostly complete: it names the exact observations and metrics returned. It could add one clarifying sentence about the suburb parameter or differentiating from price series tools, but the core usage context is still reasonably supported by the name, schema, and description.

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?

The schema shows only a required suburb_name string with no property description, and schema description coverage is 0%, so the description needed to explain this parameter. It does not: the description never mentions how suburb_name is used, what forms are accepted, or whether it requires exact or partial matching. The parameter is partly inferable from the tool name and schema, but no real semantic detail is added.

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 exactly what the tool returns: the last four weekly smart-median observations for house price, unit price, and house rent, together with week-on-week percentage change. This is specific enough to separate it from nearby siblings like suburbs_market_median_sale_price_series, suburbs_market_median_rent_series, and suburbs_market_price_growth.

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?

No guidance is given about when to prefer this tool over the many market-related siblings or when not to use it. The description tells an agent what it returns, but not why this tool should be chosen instead of, for example, a longer historical series or a broader market snapshot.

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