suggest_datasets

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

The description includes an example showing typical input and output, indicating it returns a list of matching dataset titles. It does not disclose behaviors like handling of no matches, maximum suggestions beyond the size parameter, or whether it works only for Serbian terms. Given no annotations, more behavioral detail would improve transparency.

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 extremely concise: two sentences and one example. It front-loads the purpose and provides immediate actionable guidance. Every element earns its place with zero redundancy.

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?

The tool has an output schema, so return values are documented elsewhere. The description covers the core autocomplete functionality adequately. It could mention the output schema or provide more on matching logic, but overall it 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?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds an example of usage and contextualizes the query parameter for Serbian terms, but does not provide additional meaning beyond the schema. Baseline score 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 clearly states 'Autocomplete dataset titles' and specifies the context 'when unsure of exact Serbian terms.' This effectively communicates the primary purpose and distinguishes it from exact-match search tools, though it could be more explicit in differentiating from sibling tools like search_datasets.

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 advises using the tool 'when unsure of exact Serbian terms,' providing clear usage context. However, it does not mention when not to use it or cite specific alternative tools, leaving some implicit guidance.

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