Get MQA Quality Score

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds useful behavioral details: the return includes final score, band, dataset/distribution/data service scores, and failing metrics with largest gain; fallback to previous methodology (405 scale) for not-yet-re-evaluated datasets. No contradiction.

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?

Description is densely informational but every sentence serves a purpose: main function, return details, fallback, server constraint, and workflow. Information is front-loaded (purpose first) and well-ordered. No 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?

Despite no output schema, the description fully explains return values (scores, bands, metrics) and the fallback behavior. It also clarifies what is not returned (full list) and points to the sibling for that. Complete for an agent to call 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 coverage is 100% and all parameters (dataset_id, server_url, response_format) have schema descriptions. The description adds minimal extra meaning beyond the workflow hint for dataset_id (obtained from ckan_package_show). Baseline 3 is appropriate since schema handles the heavy lifting.

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?

Description states a specific verb ('Get') and resource ('MQA quality score for a dataset'), includes the exact scale and band types, and explicitly differentiates from the sibling tool ckan_get_mqa_quality_details by noting this returns the final score and largest-gain failing metrics, while the sibling returns the full list. No ambiguity.

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?

Provides explicit constraint ('Only works with dati.gov.it server'), a typical workflow sequence (ckan_package_show → ckan_get_mqa_quality → ckan_get_mqa_quality_details), and implies when to use the sibling for full failing metrics. Clear context for selection.

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