Data Analytics MCP Toolkit

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It fails to mention that this tool likely generates a plot (implied but not stated), what format the output is in, whether it modifies data, or any performance considerations. For a tool with 5 parameters and no annotations, this is a significant gap in transparency.

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 at just one sentence with no wasted words. It's front-loaded with the core purpose, making it easy to scan. Every word earns its place by conveying essential information about what the tool does.

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, no annotations, no output schema), the description is incomplete. It doesn't explain the tool's behavior, output format, or parameter meanings. While conciseness is high, the lack of contextual details makes it inadequate for an agent to fully understand how to use this tool effectively.

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 0%, so the description must compensate by explaining parameters. It only mentions 'numeric column', which partially covers the 'column' parameter but ignores 'data_id', 'bins', 'title', and 'session_id'. This leaves most parameters undocumented, failing to add meaningful semantics beyond the bare 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's purpose as creating a histogram for a numeric column to show distribution. It specifies the verb ('Histogram') and resource ('numeric column'), distinguishing it from other plotting tools like plot_bar or plot_scatter. However, it doesn't explicitly differentiate from plot_box, which also shows distribution, leaving room for slight ambiguity.

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. It doesn't mention prerequisites (e.g., data must be loaded first), compare to other plotting tools for distribution analysis, or specify when a histogram is preferred over other visualizations like box plots. This lack of context makes it harder for an agent to select this tool appropriately.

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