Get MQA Quality Details

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds behavioral details: it returns dimension scores, non-max reasons, and raw MQA flags from data.europa.eu, and is restricted to dati.gov.it. This adds value 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 three sentences, no wasted words, front-loaded with the key action and resource. It efficiently conveys purpose, return content, server constraint, and workflow.

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 (3 parameters, no output schema, good annotations), the description covers all necessary aspects: purpose, return values, parameter constraints, server limitation, and relationship to sibling. It is fully complete for an AI agent to decide and invoke correctly.

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 baseline is 3. The description adds context: it clarifies that server_url must be a dati.gov.it base URL, explains the purpose of dataset_id, and elaborates on response_format options (markdown vs. json). This provides meaningful additional semantics.

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 'Get', the resource 'MQA quality reasons for a dataset', and distinguishes it from the sibling 'ckan_get_mqa_quality' by outlining the typical workflow (overview → details). It also specifies the server constraint (dati.gov.it) and return types.

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 provides explicit context: it is used after ckan_get_mqa_quality to inspect failing metrics, and it only works with dati.gov.it. However, it does not explicitly list when not to use it or alternatives beyond the named sibling.

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