oecd_get_education_indicator

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is clearly non-destructive. The description adds context about accessing the OECD API and returning structured data, but does not go beyond what annotations imply. No contradictions are present.

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 reasonably concise and well-structured, with a clear introduction, helpful examples, and a brief listing of arguments. It front-loads the main purpose and uses bullet points for examples. It could be slightly shorter without losing key information.

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 tool's complexity and the existence of an output schema (though not provided here), the description adequately covers the return format as markdown table or summary. It also mentions available dataflow IDs. However, it omits potential error conditions or dataset size warnings.

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 input schema provides detailed descriptions for each parameter, so the description adds limited value by simply listing parameter names. The description mentions 'dataflow_id' and 'countries' but does not elaborate on their meaning beyond what the schema already provides. With high schema coverage, a baseline 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 that the tool retrieves education data from OECD Education at a Glance report via SDMX REST API. It provides specific examples of dataflows and countries, making the purpose evident. However, it does not explicitly differentiate from sibling tools like uis_get_education_data, which serve similar but distinct data sources.

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 offers examples of usage but lacks explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or scenarios where sibling tools might be more appropriate. This omission reduces clarity for an AI agent deciding which tool to invoke.

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