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optuna

Optuna MCP Server

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by optuna

plot_rank

Generates a rank plot to visualize parameter rankings against objective values, helping identify influential hyperparameters in optimization studies.

Instructions

Return the rank plot as an image.

    Args:
        params:
            Parameter list to visualize. The default is all parameters.
        target:
            An index to specify the value to display. To plot nth objective value, set this to n.
            Note that this is 0-indexed, i.e., to plot the first objective value, set this to 0.
        target_name:
            Target’s name to display on the color bar.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo
targetNo
target_nameNoObjective Value
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states it returns an image but doesn't disclose any side effects, authorization needs, or operational constraints. The explanation of the zero-indexed target is helpful but insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose, but the following Args section is verbose and formatted like a docstring. It could be more concise, e.g., stating defaults inline rather than full parameter documentation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a plot tool with no output schema, the description covers the inputs and basic behavior. It doesn't explain what a rank plot is or the format of the image, but given sibling tools are similar visualizations, it is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description adds meaning for all three parameters: params (list to visualize, default all), target (0-indexed objective index), and target_name (color bar label). This compensates well for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Return the rank plot as an image', which is a specific verb and resource. It distinguishes itself from sibling plot tools like plot_contour, plot_slice, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains parameters in detail but does not provide guidance on when to use this tool versus alternatives (e.g., when to choose rank plot over other plots). No explicit when/not-to-use context.

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

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