select_visuals_for_kpis

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

No annotations are provided, so the description carries the full behavioral burden. 'Recommend' implies a non-mutating helper, and the Returns section sketches the output shape, but it never states side-effect freedom, cost, or whether it requires a live model connection. Adequate but with clear gaps for a zero-annotation tool.

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?

Structurally front-loaded with the purpose sentence followed by usage bullets and args. The Returns section partly duplicates the existing output schema, which is mild redundancy, but overall the text is tight and skimmable.

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?

For a four-parameter, zero-coverage, zero-annotation tool, the description covers purpose, triggers, and every argument. Since an output schema exists, the Returns prose is a bonus rather than a requirement, and only the absence of behavioral caveats keeps it from a 5.

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 0%, so the description must compensate, and it does: it documents all four parameters, enumerates the audience personas ('executive', 'analytical', 'operational'), and explains inspector as supplying column cardinality/schema info. This is well beyond what the bare schema conveys.

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 opens with a specific verb and resource: 'Recommend optimal visual types and chart configurations for given KPIs.' An agent can tell this is a recommendation/design aid rather than a mutation. It does not explicitly differentiate itself from siblings like edit_report_visual or design_report_page_from_requirements, which keeps it from a 5.

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 provides explicit trigger conditions via three 'Use this tool when the user asks to:' bullets covering chart selection, audience tailoring, and primary/alternative suggestions. There is no statement of when NOT to use it or which sibling to prefer instead, so it falls short of a 5.

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