list_datasets

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions metadata is included, which is helpful, but doesn't describe important behavioral aspects like whether this is a read-only operation (implied but not stated), what format the metadata includes, whether results are paginated (schema shows pagination parameters but description doesn't mention this), or any rate limits or authentication requirements. For a listing tool with zero annotation coverage, this leaves significant gaps.

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 a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a listing tool and front-loads the essential information. Every word earns its place, making it easy for an AI agent to quickly understand what the tool does.

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 this is a relatively simple listing tool with 2 parameters and no output schema, the description provides the basic purpose but lacks important context. It doesn't explain what 'metadata' includes, doesn't mention the pagination behavior (though parameters suggest it), and doesn't differentiate from sibling tools. While adequate for understanding the tool's basic function, there are clear gaps that could help an agent use it more effectively.

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 description coverage is 100%, with both parameters ('limit' and 'offset') well-documented in the schema itself. The description doesn't add any parameter-specific information beyond what's already in the schema. According to the scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.

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 ('List') and resource ('ONS datasets with metadata'), making the purpose immediately understandable. It distinguishes from siblings like 'get_dataset' (retrieves specific dataset) and 'search_datasets' (filters datasets), though it doesn't explicitly mention these distinctions. The description is specific enough to understand what the tool does without being tautological.

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 no guidance on when to use this tool versus alternatives like 'search_datasets' or 'get_dataset'. It doesn't mention any prerequisites, context for usage, or limitations. While the purpose is clear, there's no explicit or implied guidance about when this specific listing tool should be selected over other dataset-related tools.

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