Rank Dubai areas by gross rental yield (highest first), from official DLD sale + rental data. Great for finding the best-yielding neighbourhoods.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many areas to return (default 10, max 50). | |
| property_type | No | 'Flat' (default) or 'Villa'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. It mentions data source ('official DLD sale + rental data') and ordering ('highest first'), but lacks details on data freshness, caching, authentication requirements, or any side effects. Basic transparency is present but insufficient for a ranking tool.
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 two sentences long with no unnecessary words. It efficiently conveys purpose, data source, and use case. Every sentence adds value, making it highly concise and well-structured.
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?
The tool has no output schema and no annotations, so the description should compensate by detailing the return structure. It does not mention what fields (e.g., area name, yield value) are returned, whether results are paginated, or how to interpret the output. This leaves significant gaps for an agent invoking the tool.
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%, and both parameters are clearly described in the input schema. The description does not add additional meaning beyond what the schema provides (e.g., default and max values for 'limit', valid values for 'property_type'). Baseline 3 is appropriate since schema already handles parameter semantics.
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 clearly states the verb 'rank', the resource 'Dubai areas', and the metric 'gross rental yield (highest first)'. It also provides context about data source ('official DLD sale + rental data') and use case ('Great for finding the best-yielding neighbourhoods'). This distinguishes it from sibling tools like 'area_snapshot' or 'compare_areas'.
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 description implies usage ('Great for finding the best-yielding neighbourhoods') but does not provide explicit when-to-use or when-not-to-use guidance. It does not mention alternatives or conditions for using this tool versus siblings like 'rental_yield' or 'compare_areas'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: listing areas, getting area snapshot, comparing areas, market overview, affordability calculation, yield ranking, and rental yield. No overlap or ambiguity.
All tool names follow a consistent pattern of lowercase snake_case with verbs like 'list', 'compare', 'rank', 'get' (implied in area_snapshot). Very predictable.
Seven tools are well-scoped for a Dubai real estate data server. Each tool adds distinct value without redundancy, fitting the ideal range of 3-15.
The set covers essential operations: listing areas, detailed snapshots, comparisons, market overview, affordability filtering, and yield analysis. No obvious gaps for the domain.