plot_qq

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

The description discloses the output format (JSON + inline PNG) but offers no other behavioral traits. With no annotations, it fails to indicate whether the operation is read-only, any side effects, or data type requirements, leaving a significant transparency 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?

The description is extremely concise, using only two sentence fragments. It contains no superfluous words and directly conveys the plot type and output format, which is efficient for a simple tool.

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?

While the tool is simple, the description omits essential context such as expected column types, what the JSON contains, and when to prefer this over other plot tools. The absence of an output schema makes the vague reference to JSON insufficient for full comprehension.

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?

The schema defines two required parameters, column and source_id, but the description provides no explanation of their meaning or usage. With 0% schema description coverage, the description should compensate, but it does not mention parameters at all.

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 the tool creates a Q-Q plot versus a normal distribution, which is a specific plot type that distinguishes it from other plot tools like plot_scatter or plot_distribution. It also mentions the output format (JSON + inline PNG), further clarifying its purpose.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention it is for checking normality, nor does it exclude other use cases, leaving the agent without clear decision support.

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