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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false. The description adds meaningful behavioral context beyond those: the server applies the same chartability gate as request_chart, every result carries chartable_reason, and auth restrictions produce a 403 for non-admins. No contradiction with annotations exists.

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 dense but efficient; nearly every sentence adds distinct value such as auth, filtering, workflow, and return fields. Minor redundancy exists between "admin only" and "Non-admin keys receive 403," and the opening label is slightly verbose, but overall it is well-structured and front-loaded.

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?

With no output schema, the description compensates by naming all returned fields (dataset_id, chartable, chartable_reason, title, publisher, topic, unit, quality_tier). It also covers auth behavior, filtering semantics, ranking, and the follow-up pipeline, making the tool fully actionable for an agent without needing additional context.

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% for the single limit parameter, including default and max values, so the description does not need to add much. It contributes only the context that results are ranked by relevance, which is implied but not schema-documented. This matches the baseline-3 expectation when the schema already fully describes parameters.

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 and resource: list catalog datasets with no published chart yet, pre-filtered as chartable and ranked by relevance. It clearly differentiates this tool from sibling tools like list_charts (published charts) and request_chart (single dataset request) by framing it as the internal queue for autario-generated charts.

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?

It explicitly states the tool is admin-only, that non-admin keys receive 403, and that third parties do not need it. It also gives a direct workflow for each returned dataset (request_chart preferred, otherwise get_dataset_info -> get_dataset_schema -> query_dataset -> create_chart_from_spec) and explains why the queue avoids the no_usable_series / sparse_multi_entity_data failures of request_chart.

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