Line Chart

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

Annotations already indicate readOnlyHint and idempotentHint, so the safety profile is clear. The description adds the dependency note (requires matplotlib), but does not detail what the tool returns (e.g., whether it displays a chart or returns a figure). Minor gap.

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?

Concise with a clear purpose sentence, a usage note, and two illustrative examples. No wasted words; information is front-loaded.

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 full schema coverage and annotations, the description adequately covers purpose, usage, and examples. However, it does not specify the output format (e.g., returns a matplotlib figure or displays the chart), which would improve completeness for a tool with no output schema.

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 descriptions cover 100% of parameters with clear examples and defaults. The description does not add new parameter details beyond the schema; examples illustrate usage but do not enhance parameter understanding significantly.

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 chart from data points and specifies it is for general XY data. It distinguishes from the sibling tool plot_financial_line.

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?

Provides explicit guidance on when to use (general XY data) and when not to use (time-series price data with moving average, suggesting plot_financial_line instead). Also mentions the dependency on matplotlib.

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