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

The annotations already cover read-only, idempotent, non-destructive and closed-world behavior, and the description goes well beyond them: it discloses the data provenance (Dubai Land Department open data), daily refresh cadence, the CC BY 4.0 license, the truncation caveat on monthly price history, and the citation obligation to link the returned `url`. For a read-only statistics tool this is unusually rich behavioral 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?

Front-loads the core action and the slug prerequisite in the first sentence, then layers the type enumeration, returned fields and data provenance. The 'Data:' sentence is dense but every clause earns its place; it is somewhat list-heavy rather than sparse, but nothing is redundant.

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?

With no output schema, the description compensates by enumerating the returned fields (price and AED/sqft medians, YoY changes, off-plan share, bedroom breakdown, monthly price history, developer projects). Provenance and truncation are covered, but it says nothing about behavior when the slug is unknown or invalid, which an agent would want to know.

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 0%, so the description must carry the load, and it does: it defines the valid `type` values (project | community | developer | area) and explains that `slug` is an entity identifier that must first be resolved via `search`. It also notes that developer entities additionally return their projects. The only gap is any statement of slug format or case sensitivity.

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 ('Get the full statistics record for one project, community, developer or area by slug') and enumerates exactly which entity kinds are valid. It also names the sibling `search` tool that supplies the slug, so an agent can distinguish retrieval from discovery without opening any schema.

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?

Explicitly routes the agent to `search` to obtain the slug, which is the key prerequisite for calling this tool. It gives clear context for use, but does not say when to prefer a sibling such as get_market_summary or get_monthly_report over this one, so the boundary against those tools is left implicit.

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