plot_line

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It reveals that multiple y columns can be overlaid and that sorting matters, but it does not mention expected input format, whether it renders inline or saves, or any side effects. For a plotting tool, this is an acceptable but incomplete disclosure.

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 reasonably sized but includes redundancy: 'For time-series data and trends' and 'Supports multiple y columns overlaid' are each repeated. While examples are useful, the repetition adds no value and could be tightened.

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 description covers purpose, usage, and key parameters, but lacks information about df_name and save_path, and does not explain what the tool returns (e.g., a plot object, file, or display). Given no output schema and no annotations, this leaves moderate gaps for an agent to fully understand the tool's behavior.

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. The examples clarify the semantics of x, y, and hue (e.g., plot_line(x='date', y=['Revenue','Cost'], hue='Category')). However, df_name and save_path are not explained, leaving their purpose ambiguous.

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 line plot and emphasizes its use for time-series and trends, distinguishing it from other plot types (e.g., scatter, bar). The examples demonstrate the intended output, though the opening 'Line plot' is somewhat redundant with the name.

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 specifies when to use the tool ('For time-series data and trends') and provides a key prerequisite ('Sort data by x-axis column first'). It does not explicitly list alternatives or when-not-to-use, but the context is clear enough for an agent to select this over sibling plot tools.

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