plot_generate_code

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

The annotations already establish readOnlyHint=true, and the description aligns by saying it generates code rather than mutating data. It adds useful context that the output is Python plotting code, but it does not describe the output format, whether the code is standalone, or any limitations beyond what the annotations and output schema already imply.

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 a single, front-loaded sentence with no filler, repetition, or redundant content. It communicates the action, resource, and purpose efficiently, which is ideal for an agent scanning tool descriptions.

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?

The tool is low complexity: all three required parameters are fully described in the schema and an output schema is present, so the description does not need to restate parameters or return values. The remaining gap is the lack of explicit differentiation from plot_comparison_notebook, which prevents a perfect score.

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 100%, so all three parameters are already documented with types and descriptions in the input schema. The description adds only the high-level 'measurement comparison' framing and no additional detail about how the parameters relate to one another, so the baseline score of 3 is appropriate.

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 identifies the action ('Generate') and the resource ('Python plotting code') and adds the purpose 'for measurement comparison.' It does not explicitly name sibling tools, but the focus on Python plotting code distinguishes it from notebook-oriented or data-fetching siblings such as plot_comparison_notebook and data_generate_fetcher_script.

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 phrase 'for measurement comparison' implies when the tool is appropriate, but there is no explicit guidance about when to use it versus plot_comparison_notebook or other plotting/code-generation siblings, and no exclusions are stated. This is adequate but leaves the choice to inference.

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