ABS monthly unemployment rate (6202.0). Regions: National, NSW, VIC, QLD, SA, WA, TAS. State aliases accepted (e.g. 'New South Wales'->NSW). NT/ACT not available from the ABS LF flow (returns 404 'no data').
| Name | Required | Description | Default |
|---|---|---|---|
| region | No | National, NSW, VIC, QLD, SA, WA, or TAS (NT/ACT have no 6202.0 series) |
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 usefully discloses that state aliases are accepted and that NT/ACT returns a 404 'no data' error, but it does not describe the output format, units, default behavior when region is omitted, or whether historical series are returned.
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 four short, information-dense sentences. Every sentence contributes either the core purpose, allowed values, alias behavior, or a notable error condition, with no filler 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?
For a single-parameter lookup tool, the description covers source, regions, aliases, and an important limitation. However, there is no output schema and the description does not specify what the tool returns (e.g., latest value, time series, percentage), nor the default behavior when the optional region parameter is omitted.
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 already provides 100% coverage for the region parameter, so the baseline is 3. The description adds value beyond the schema by explaining that state aliases are normalized (e.g., 'New South Wales' -> NSW) and that NT/ACT is not supported, clarifying the parameter's practical behavior.
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 as providing the ABS monthly unemployment rate (6202.0), which distinguishes it from sibling tools like au-cpi or au-awe. It lacks an explicit verb like 'returns' or 'gets', but the resource and scope are unambiguous.
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 for monthly unemployment rate lookups and explicitly lists allowed regions plus NT/ACT exclusion. However, it does not name alternative tools or provide explicit 'use this when...' versus 'use that when...' guidance, leaving the selection logic somewhat implicit.
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.
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.
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.
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.
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.