marginsplot

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

Annotations already declare readOnlyHint=true and the plot description is consistent with a non-mutating operation, so there is no contradiction. The description adds only that confidence intervals are included; it does not disclose rendering behavior, failure modes, or relationship to a fitted margins result, but the annotation lowers the burden.

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 one short, front-loaded sentence with no filler or repetition. It is concise but slightly thin; a brief note on expected input or relationship to margins() would make it more useful without hurting conciseness.

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 simple plotting tool with a required margins_df parameter, a full output schema, and read-only annotations, the definition is minimally usable. However, the existence of many plotting/plot-adjacent siblings and the lack of any statement about when this tool is appropriate leaves a completeness gap for tool selection.

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 the baseline of 3 applies; the tool description adds no parameter-level meaning. The schema's margins_df entry is informative, but that is structured data rather than narrative value from the description.

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 clear verb ('Plot') and resource ('marginal effects with confidence intervals'), so an agent can see this is a visualization tool. It does not differentiate it from sibling tools such as margins_at_plot or plot_from_result, but the core action is unambiguous.

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?

There is no guidance on when to use this tool instead of margins_at_plot, plot_from_result, or margins_table. The schema notes that margins_df is output from margins(), but the description itself gives no context, exclusions, or alternative routing.

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