text_to_images

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

No annotations are present, so the description must disclose behavioral traits. It only enumerates themes and ratios, but fails to mention return format, side effects (e.g., file creation via outputDir), authentication needs (e.g., Gemini API key for generateAiCover), or output structure. The description adds no behavioral context beyond the schema's parameter descriptions.

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 concise and well-structured: a one-sentence purpose immediately followed by clean bullet lists for themes and ratios. Every item earns its place by explaining the options. However, it omits important behavioral details, but that is a completeness issue, not a conciseness one. It is front-loaded and 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?

With 9 parameters, no annotations, and no output schema, the description bears significant responsibility. It covers only two parameters (theme and ratio) and ignores the rest, including outputDir behavior, AI cover generation, font size, and the relationship between text length and pagination. Missing usage guidance and return format makes it incomplete for a tool of this complexity.

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 100%, so the baseline is 3. The description enriches the enum parameters 'theme' and 'ratio' with human-readable explanations and usage recommendations (e.g., 'minimal: Clean white background, good for knowledge/tips content'), which adds semantic value beyond the bare schema. Other parameters like outputDir and generateAiCover are not mentioned, but their schema descriptions are sufficient.

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's purpose: 'Convert text content to a series of images with Xiaohongshu style themes.' It uses a specific verb+resource construction that distinguishes it from typical image tools. However, it does not explicitly differentiate from sibling tools like file_to_images or estimate_pages, so it stops short of a 5.

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?

There is no guidance on when to use this tool versus the sibling tools (e.g., file_to_images, estimate_pages). The description provides context for theme/ratio selection but lacks any 'when to use' or 'when not to use' direction, leaving the agent to infer usage from the tool name alone.

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