search_datasets

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

With no annotations, the description carries the burden for safety and behavior. It discloses the return type (matched datasets with IDs, sources, example queries) and provides natural-language examples, but it does not mention potential limitations (e.g., returns only catalog metadata, not data values), ordering, or any side effects. This is adequate but not deeply transparent.

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 two sentences plus a terse example list. It leads with the main verb and object, immediately states the return payload, and gives usage guidance. Every sentence earns its place with no filler.

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 straightforward search tool, the description covers purpose, return value, and use case. There is no output schema, but the description tells the agent what to expect. It could be slightly more complete by noting the effect of the 'limit' parameter or the fact that it searches catalog metadata only, but the provided context is sufficient for a simple tool.

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 descriptions for both 'q' and 'limit' are fully self-explanatory with examples, types, defaults, and constraints. Since schema coverage is 100%, the description adds no additional parameter-level semantics beyond reiterating examples, so the baseline of 3 applies.

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 states the verb 'Search' plus the specific resource 'catalog of curated Australian government datasets'. It distinguishes itself from sibling tools by focusing on searching when the dataset_id is unknown, and it mentions the return content (IDs, sources, example queries), making its purpose unmistakable.

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 explicitly states the primary usage scenario: 'Use this when you don't know the exact dataset_id'. This is clear practical guidance, though it does not explicitly name alternative tools (e.g., list_datasets) or provide direct when-not-to-use conditions.

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