enhance_chart_tooltips

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

With no annotations, the description carries full burden. It explains that the tool modifies hover information and returns an enhanced figure dict. It does not mention side effects like mutating the original figure or limitations, but the behavior is sufficiently disclosed for typical understanding.

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 extremely concise: two sentences stating purpose, a one-line example, and a return type declaration. Every part is informative with no fluff.

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?

Given the complexity (5 parameters, output schema exists), the description covers what the tool does, how parameters affect output, and what is returned. Combined with parameter descriptions, it is fully complete for an agent to select and invoke 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% with parameter descriptions. The tool description adds value by explaining how parameters like show_mean, show_rank, unit, and value_column affect the tooltip content, including example formatting. This goes beyond the schema definitions.

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 clearly states the tool adds rich contextual tooltips to Plotly figures. It provides a before/after example and mentions specific enrichments (formatted values, deviation from mean, rank). This distinguishes it from siblings like add_chart_annotation or add_chart_callouts, which serve different purposes.

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?

The description implicitly suggests using this tool after creating a chart to enhance tooltips. However, it does not explicitly state when to use versus alternative tools or when not to use it. The context is clear enough for typical use, but lacks explicit exclusions.

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