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

Annotations already state readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds useful return-scope detail by listing the dataset fields exposed, though it does not mention missing-slug behavior, auth requirements, or rate limits.

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 front-loaded sentence with no filler, and the return-field list is relevant. The long comma-separated enumeration is dense but still efficient.

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 one-parameter read-only lookup with no output schema, the description sufficiently explains what is returned. Annotations cover safety traits, though the description could ideally mention behavior when the slug is unknown.

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% and the slug parameter includes concrete examples, so the schema does the heavy lifting. The description adds no syntax or format guidance beyond what the schema provides, making the baseline 3 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 names a specific retrieval operation and resource: full details for one DataClue dataset. It clearly distinguishes a single-dataset lookup from a broad search, though it does not explicitly name siblings 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?

Usage is only implied by “one DataClue dataset” and the required slug parameter, suggesting it is for when the slug is already known. It gives no explicit when-to-use guidance or comparison with search_datasets, get_pricing_and_terms, or request_quote.

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