plot_interactive_correlation_heatmap

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

With no annotations, the description carries full burden. It explains method options and column_filter behavior but omits details like data_file_path requirements, handling of non-numeric columns, or output format. Basic but not fully transparent.

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 concise with five focused sentences. The first sentence states the core purpose, followed by usage and parameter details. No redundant or unnecessary text.

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 tool's moderate complexity (4 params, output schema exists), the description covers essential aspects. It could mention that data_file_path should point to a CSV or similar, and title is for the plot title. Overall adequate but not exhaustive.

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 0%, so description compensates by explaining method (must be 'pearson' or 'spearman') and column_filter (comma-separated names/patterns). Title and data_file_path lack additional explanation, but overall adds significant meaning beyond schema.

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 generates an interactive Plotly correlation heatmap for visualizing relationships between numeric features. It is distinct from sibling tools like plot_static_correlation_heatmap and run_correlation.

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 says 'Use this to visualize relationships between numeric features,' providing clear context. It does not explicitly exclude alternatives, but given sibling context, the purpose is well-defined.

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