list_dataflows

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

With no annotations, the description carries full burden but only states basic list/filter functionality. It does not disclose behavioral traits such as pagination, sorting, rate limits, or what happens with no results. Minimal disclosure.

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?

Two sentences with no wasted words. The purpose and optional filter are stated upfront, making it 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?

For a simple list tool with two optional parameters and no output schema, the description is fairly complete. It provides enough context for browsing, though it could mention the return format (e.g., list of names/IDs).

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%, and the description adds marginal meaning by linking category filtering to browsing by topic area. However, it does not provide new syntax or format details beyond the schema, so 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 verb 'List' and resource 'OECD dataflows (datasets)', and clarifies optional filtering by category. It effectively distinguishes from siblings like 'get_categories' and 'search_dataflows' by focusing on browsing datasets by topic area.

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 implies usage for browsing datasets by topic area but does not provide explicit guidance on when to use this tool versus alternatives like 'search_dataflows' or conditions to avoid. No exclusion criteria or alternative recommendations are given.

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