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

Annotations already cover read-only, idempotent and closed-world behavior, so the description's job is to add context — and it does, disclosing the parse-then-return pipeline and that results are schema.org-typed with mrk.ae URLs. It omits pagination/limit behavior and any note on what happens when the query parses to nothing.

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?

Two sentences with no waste: the example is front-loaded as the first concrete detail, followed by the parse-and-return contract. Nothing is repeated from the schema or annotations.

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 two-parameter read tool with full schema coverage and an example, this is nearly complete; the return format is sketched even though no output schema exists. Only empty-result and limit-interaction behavior go unmentioned.

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 both q and limit are already documented; the baseline would be 3. The description earns the extra point by enumerating the attributes the q string is parsed for (community, developer, bedrooms, price, stage, handover year, type), which tells an agent how to phrase the query.

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?

States a specific verb and resource ('answer a free-text Dubai property question') plus a concrete example query, which separates it from the structured siblings like search_listings and search_projects. The parsed-attribute list further pins down what the tool does.

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?

The free-text framing and the worked example make clear this is for natural-language, multi-criteria queries, implying structured searches belong to the listing/project tools. It never names an alternative or an explicit when-not condition, so the guidance stops short of a 5.

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