get_dataflow_url

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

No annotations are provided, so the description carries full burden. It fails to state that the tool is read-only, non-destructive, or what happens on invalid input. It also does not describe the return value (a URL string) beyond the implication.

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 two concise sentences with the verb and resource front-loaded. Every word serves a purpose, with no redundant or vague phrasing.

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 is simple, but the description omits the return value format (a URL string). Since there is no output schema, mentioning the return type would enhance completeness. The schema coverage for parameters is complete.

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% as both parameters have descriptions in the schema. The description adds no extra detail beyond the schema's 'Dataflow ID' and 'Optional dimension filter', so the 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 the action ('Generate') and the resource ('OECD Data Explorer URL for a dataset'). It distinguishes this tool from sibling tools (e.g., get_categories, list_dataflows) which focus on listing or querying data, not generating URLs for visual exploration.

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 specifies the use case: 'to provide users with a direct link to explore data visually in their browser.' While it doesn't explicitly mention when not to use it, the sibling tools are sufficiently different, making the usage context clear.

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