Given a budget in AED, list Dubai areas where the median sale price fits (largest you can afford first).
| Name | Required | Description | Default |
|---|---|---|---|
| budget_aed | Yes | Budget in AED, e.g. 1500000. | |
| property_type | No | 'Flat' (default) or 'Villa'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the core behavior (listing areas by median sale price fitting budget, sorted descending), but lacks details on edge cases like no matching areas or handling of invalid input. It also does not mention the data source or any side effects.
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 a single, well-structured sentence that is front-loaded with the condition and action. No unnecessary words or repetition.
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 the simplicity of the tool and lack of output schema, the description adequately explains input and high-level output. However, it does not specify what information is shown for each area (e.g., price, name only) or the exact ordering logic, which could be clarified.
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 baseline is 3. The description adds context by stating the budget is in AED and that property_type defaults to 'Flat', but these are already in the schema descriptions. No additional semantic enrichment beyond what the schema provides.
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 identifies the tool's purpose: given a budget in AED, list Dubai areas where the median sale price fits, ordered by largest affordable first. This verb-resource pairing is specific and distinct from sibling tools like compare_areas or market_overview.
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 when a user wants to find affordable areas within a budget, but it does not explicitly state when not to use it or provide direct alternatives. The sibling tools are listed externally but not referenced.
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.