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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond the annotations: it notes that data comes from the OECD SDMX public REST API with no authentication required. This helps the agent understand prerequisites and expected behavior.

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 concise and well-structured: it front-loads the purpose, provides a concrete example, explains the use case, and closes with source and authentication info. Every sentence earns its place without redundancy.

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 the presence of an output schema and annotations that cover safety, the description is complete. It covers the what, why, when-to-use, source, and authentication requirements. An agent has all the information needed to select and correctly invoke this tool.

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%, so the baseline is 3. The description adds meaning beyond the schema by explaining that the returned codes cover 'reference area, frequency, measure, and breakdown dimensions' and that the parameters should come from oecd-data.dataflows. This enriches the agent's mental model of the parameters and their relationship to the output.

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 states a specific verb ('Get') and resource ('dimensions and valid codes for an OECD dataflow'), and provides a concrete example with both required parameters. It clearly distinguishes this structure tool from the data-retrieval tool by explaining its role in interpreting dimension labels.

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 explicitly explains when to use this tool: to interpret dimension labels returned by oecd-data.data or to build a narrower key filter. It does not explicitly name alternative tools or state when not to use it, but the provided usage context is sufficient for an agent to disambiguate.

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