Get the figure-design reasoning prompt

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states that embedding the article modifies the prompt, but does not mention potential side effects, idempotency, rate limits, or authentication requirements. For a tool that likely has no destructive side effects, this is adequate but not complete.

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 a single paragraph of four sentences, front-loaded with the core purpose. Each sentence provides necessary information: what the prompt does, how to pass the article, what to do with the output. It is concise without omitting critical details.

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 tool returns a prompt for figure creation, the description explains the overall workflow and references sibling tools (render_figure, render_cover). It does not describe the output schema or prompt format, but that is reasonable for a prompt-returning tool. It covers the key context for use.

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 coverage is 0%, so the description must compensate. It explains that title, excerpt, and body_text are parts of the article to embed in the prompt, and that omitting all of them yields a different output (rules + template menu). This adds significant meaning beyond the parameter names alone.

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 that the tool returns a reasoning prompt for turning an article into figures and a cover, with specific details about template selection and sentence anchoring. It distinguishes itself from sibling tools like render_figure and render_cover by indicating that this tool produces the prompt to guide those subsequent calls.

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 explicitly tells when to pass article parameters (to get the full prompt) and when to omit them (to get just the rules and template menu). It also provides the downstream workflow: use the prompt to produce figure-spec JSON, then call render_figure/render_cover. This covers both usage scenarios and next steps.

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