quick_plot

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

With no annotations, the description carries full behavioral burden. It explains that the server validates the figure and returns a JSON string, and justifies the string format for robustness. However, it omits details on authorization, rate limits, side effects, or error states.

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 four sentences, front-loaded with the core purpose. It is efficient but includes a slightly redundant justification about robustness. All sentences add value; no filler.

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 the existence of an output schema, the description adequately covers return format. However, with three siblings listed, it lacks comparative guidance, making it less complete for an agent choosing among tools.

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 baseline is 3. The description adds a high-level usage statement ('pass data as a list of records and choose a chart kind') but does not enrich parameter semantics beyond what the schema already provides. No additional nuance for x, y, color, or title.

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 builds an interactive Plotly figure and returns JSON, distinguishing it from siblings that output HTML (render_figure_html) or describe plots (describe_plot). The use of 'return it as JSON' and 'frontend can parse' differentiates the output format.

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 tells how to use the tool (pass data as records, choose kind) but provides no guidance on when to use this tool versus siblings like create_figure or render_figure_html. No exclusions or contexts are mentioned.

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