create_visualization

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

Annotations only supply destructiveHint=true, so the description does real work: it discloses that the call returns the new visualization's id and enumerates the ordered dependencies with create_query and add_widget. It does not explain why a creation tool carries a destructive hint or what state it mutates, leaving a small gap, but the workflow and return-value disclosure are well beyond what annotations provide.

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?

Four short, front-loaded sentences with explicit Behavior and Usage labels; every sentence conveys either output, prerequisite, or next step, and none restate the schema.

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 correctly discloses the return value (the new id), and it covers the full create-then-widget sequence. For an 8-parameter tool with complete schema coverage, nothing essential for a correct call is missing.

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%, so the baseline is 3; the description earns above that by adding a constraint the schema omits: column names (x_column, y_columns, series_column) must exactly match the saved query's result columns, and points at get_query_result to discover them. That is semantic guidance beyond the field descriptions.

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 first sentence gives a specific verb (create) and resource (chart/counter) and enumerates every supported chart type, so an agent knows exactly what will be produced. It also implicitly distinguishes itself from siblings create_query and add_widget by naming them in the workflow.

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?

Explicit when-to-use plumbing: save the SQL with create_query first, verify column names via get_query_result, and call add_widget afterwards to place it on a dashboard. The condition that column names must exactly match result columns is a concrete prerequisite, not an inference.

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