search_datasets

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

With no annotations, the description explains it is fuzzy-search, case-insensitive, matches against multiple fields, returns ranked results with specific fields. It does not cover edge cases (no results, errors) or performance, but is transparent enough for typical use.

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 concise, front-loaded with the main purpose, followed by context, examples, and return type. Every sentence adds value, and the structure is easy to parse.

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, the description covers the search behavior and return fields adequately. It could mention the default and maximum limit, but overall it provides enough context for an agent to use the tool correctly.

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 coverage is 100%, so baseline is 3. The description repeats schema info (e.g., 'Free-text search query' and limits). It adds no new semantic meaning beyond what is already in the input 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 the tool does 'Fuzzy-search the curated ATO/ACNC dataset catalog', which is a specific verb and resource. It distinguishes itself from siblings like describe_dataset or get_data by focusing on search and discovery. The examples further clarify the purpose.

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 provides relevant examples and mentions the catalog contents, but does not explicitly state when to use this tool vs alternatives (e.g., list_curated may be for listing without a query). The guidance is adequate but lacks exclusion criteria.

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