search_datasets

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

With no annotations, the description explains that the search is fuzzy, case-insensitive, and returns ranked results. It does not explicitly state read-only or safe behavior, but the examples and return type imply no destructive side effects. Could be more transparent about permissions or performance.

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 well-structured with a clear purpose, list of included datasets, examples, and return type. It is slightly verbose but each section serves a purpose. Front-loading the main verb and resource is effective.

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?

Given the presence of an output schema and the description's explanation of return fields (DatasetSummary), the description is fairly complete. It covers the tool's scope, usage, and examples, though it could benefit from mentioning if there are any limitations or prerequisites.

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?

Schema description coverage is 100%, with clear descriptions for both 'query' and 'limit' parameters. The tool description adds examples and context about the catalog but does not significantly enhance understanding beyond the schema.

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 it's a fuzzy-search tool for a curated APRA dataset catalog, lists example datasets, and provides usage examples. It distinguishes from siblings like describe_dataset and list_curated by focusing on discovery via free-text search.

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 when to use (to find datasets) but does not explicitly contrast with sibling tools or state when not to use it. No direct guidance on alternatives, leaving the agent to infer context.

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