generate_line_chart

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

With no annotations provided, the description carries full burden of behavioral disclosure. It explains that y_column values are 'summed per X value', that group_by draws one line per group, and that filename is auto-generated if empty. It also specifies the return format as a JSON string with chart_path and chart_data. These are meaningful behavioral traits beyond what the schema states, though it does not discuss error handling or side effects.

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 organized as a docstring with a one-line purpose statement followed by a labeled Args section and a Returns section. It is concise with no fluff—every sentence provides functional information. The structure is clean and front-loaded, making key parameters easy to scan.

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 all six parameters, their roles, return format, and grouping behavior. Since an output schema is provided (the JSON structure), the description need not explain return values further. It adequately addresses the tool's complexity for an agent to invoke it correctly, including how y values are aggregated and how group_by affects rendering.

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 fully compensates. Each parameter gets a meaningful explanation: dataset is a name, x_column is 'ideally a date or ordered category', y_column is 'numeric' and 'summed per X value', group_by is 'optional column to draw one line per group', and filename has auto-generation behavior. This adds substantial semantic value over 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 states a clear verb and resource: 'Generate a line chart'. It also cites the primary use case ('great for time series or trends'), which differentiates it from sibling chart tools like pie or scatter plots. The verb-resource combination is specific and unambiguous.

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 gives clear context on when to use the tool ('great for time series or trends'), which implies the appropriate scenario. However, it does not explicitly name alternatives or state when not to use it. No exclusions or trade-offs are discussed, so it stops short of a 5.

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