oecd_list_education_datasets

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

Annotations already convey read-only, idempotent, and open-world nature. The description adds value by specifying the return format (Markdown list with descriptions and dataflow IDs) and the scope (OECD countries plus partners), which goes beyond the annotations.

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 well-structured with bullet points and clear sections. It front-loads the main purpose. Slightly verbose in the topic area listing but overall concise and 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?

Given no parameters, an output schema exists, and rich annotations, the description covers purpose and return value well. However, it lacks guidance on when to use relative to siblings, which slightly detracts from completeness.

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 tool has zero parameters, and the schema coverage is 100% (trivially). The description does not need to add parameter semantics, and the baseline for 0 parameters is 4. It doesn't detract from this score.

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 it lists available OECD Education at a Glance datasets, specifying the resource and action. It enumerates topic areas with example dataflow IDs, effectively distinguishing it from sibling tools like oecd_get_education_indicator or uis_list_countries.

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 does not provide explicit guidance on when to use this tool versus alternatives. No context about prerequisites or exclusions, such as when a more specific tool like oecd_search_datasets might be appropriate.

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