Data Analytics MCP Toolkit

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

With no annotations provided, the description carries full burden but offers minimal behavioral information. It mentions the default column behavior but doesn't disclose whether this is a read-only operation, what permissions are needed, how the plot is displayed/returned, or any performance considerations. For a visualization tool with 4 parameters, this is insufficient.

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 with just two sentences that directly address the tool's core functionality and one parameter behavior. Every word earns its place with zero wasted text, though this conciseness comes at the cost of completeness.

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 visualization tool with 4 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns (plot format, file, display), how to interpret results, or provide sufficient parameter guidance. The minimal description leaves too many gaps for effective tool use.

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?

With 0% schema description coverage and 4 parameters, the description only partially addresses the 'columns' parameter behavior. It doesn't explain data_id (required parameter), title, or session_id. The description adds minimal value beyond the bare schema, failing to compensate for the complete lack of schema 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 description clearly states the tool creates a 'Heatmap of correlation matrix' with a specific behavior when columns are omitted ('uses all numeric columns'). This provides a specific verb ('plot') and resource ('correlation matrix'), though it doesn't explicitly distinguish from sibling plotting tools like plot_bar or plot_scatter.

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 provides no guidance on when to use this tool versus alternatives like plot_scatter for correlation visualization or other plotting tools. It mentions the default behavior when columns are omitted but doesn't specify use cases, prerequisites, or exclusions.

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