Skip to main content
Glama

Data To Agents

list_services

List data services offered by this server: ids, countries, prices, and required params. Optional country filter (ISO 3166-1 alpha-2, e.g. "AU", "US", "GB"). Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNoISO 3166-1 alpha-2 country code filter, e.g. "AU"

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the burden. 'List' implies a safe read operation, and 'Free' discloses cost, while the listed fields describe the response. However, it does not confirm absence of side effects, pagination behavior, or what happens when the country filter matches nothing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences: the first front-loads the purpose and return contents, the second covers filtering and cost. No filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, parameterless-required list tool, the description covers what the agent needs: what is listed, the optional filter, and pricing. Since no output schema exists, the explicit mention of response fields (ids, countries, prices, required params) is helpful, though a bit more detail on return shape would make it fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds the word 'optional,' the ISO standard, and multiple example codes, but these are largely redundant with the schema's own parameter description and length constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Uses a specific verb ('List') and resource ('data services offered by this server'), and enumerates exactly what the response covers (ids, countries, prices, required params). This clearly distinguishes it from the sibling data-service tools, which are the things being listed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

States the optional country filter, gives the ISO format with examples, and notes that the tool is free. The intended use as a catalog/discovery tool is clear from context, though it does not explicitly name alternatives or say when not to use it.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation5/5

Every tool maps to a clearly distinct dataset or lookup, with country prefixes and topic names separating overlapping domains. Even similar tools like au-abs-building-activity and au-abs-building-approvals are unambiguously differentiated by their descriptions.

Naming Consistency4/5

The data tools follow a consistent country/topic hyphenated pattern (au-*, nz-*), making resource selection predictable. The meta tools (get_catalog, list_services, health) break this pattern with imperative/underscore names, but this is a minor and understandable deviation.

Tool Count3/5

At 26 tools, the set is on the heavy side and slightly exceeds the typical comfortable range. However, each tool represents a genuinely distinct data service, and the clear grouping by country and topic keeps the surface navigable.

Completeness4/5

The server covers a broad range of common agent data needs for Australia and New Zealand: demographics, income, building, labour, weather, time, holidays, school terms, and place resolution. Minor gaps exist, such as no NZ building data or broader international coverage, but core workflows are well supported.

Resources