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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds valuable extra context beyond those annotations: it names the underlying data source (CKAN Action API), states that no auth is required, and flags that the output is reference-only and not usable as a dataset_search filter.

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 three sentences with no filler. It front-loads the core purpose and return value, then gives the critical caveat about not being usable as a dataset_search filter, then closes with source and auth details. Every sentence contributes useful information.

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?

This is a simple tool with one optional parameter, a rich output schema, and annotations covering safety and idempotency. The description completes the picture by covering purpose, the browse-only caveat, data source, and authentication requirements. Nothing needed to select or call the tool correctly is missing.

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 input schema already documents the single optional query parameter as 'Substring filter on subject slug (e.g. "health")'. The description adds that filtering is optional and substring-based, but this largely restates the schema. With 100% schema description coverage, the baseline of 3 is appropriate.

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 states a specific verb ('List'), a specific resource (the Australian Government open data AGIFT subject taxonomy), and what is returned (current dataset count per subject) with an optional substring filter. It also distinguishes itself from dataset_search by explicitly saying it is not usable as a dataset_search filter, making its role clear.

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 gives clear context for when the tool is appropriate: it is a browse-only reference for subject taxonomy, not a dataset search filter. It does not explicitly name an alternative tool such as au-data-gov.datasets.search, but the exclusion is concrete enough to prevent obvious misuse.

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