UN-Habitat — Global Municipal Budget Database

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description need not restate safety. It adds useful context about data coverage (1,207 cities) and field breadth, which goes beyond annotations. However, it does not disclose any additional behavioral traits such as response pagination, data vintage, or filter combination semantics; the output schema covers return format, so this is acceptable but not exceptional.

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 compact and information-dense. It front-loads the core action and resource, then lists data fields, filters, and use case in a logical flow. Every sentence contributes value; there is no fluff or repetition of schema details. The length is appropriate for the tool's breadth.

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 read-only query tool with all optional parametersholidays, an output schema, and safety annotations, the description is fully sufficient. It explains what data is available, how many cities, what fields, and what filters exist. The addition of income group (even without a filter) hints at data richness. No critical information is missing for an agent to invoke this tool correctly.

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 provides 100% description coverage for all four parameters, including partial-match and case-insensitivity notes, defaults, and ranges. The description merely restates 'Filter by country, city, or UN region' without adding new meaning. It also mentions income group as data content but offers no parameter for it, which is a minor ambiguity. Schema already carries the semantic weight.

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 opens with the specific action 'Retrieve municipal budget and expenditure data' and names the exact resource ('UN-Habitat Global Municipal Database'), which immediately distinguishes it from other urban data tools like land_consumption or transport_access. It further lists precise data fields (total budget, per capita, capital expenditure, own-source revenue, sector percentages), leaving no ambiguity about the tool's scope.

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 states the intended application ('Useful for comparative municipal finance analysis and urban governance research') and clearly enumerates the available filters (country, city, UN region). It does not explicitly contrast with sibling tools, but the data scope and filter options make suitable use cases obvious. No exclusions are given, but none are necessary for a read-only query tool.

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