canvas_render_layout

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

Beyond annotations (idempotentHint=true), the description labels it as a deterministic renderer (not AI generation) and adds a mandatory post-invocation instruction to open the image in Preview, which is valuable behavioral guidance.

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?

Well-structured with clear sections, concise sentences, and no redundancy. Every sentence adds value, and the important post-invocation note is highlighted.

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 parameter complexity and presence of an output schema, the description covers when to use, an example, and a critical post-invocation step. Lacks error handling info, but the output schema fills return value gaps.

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?

Despite 0% schema description coverage, the schema itself has detailed property descriptions. The description adds a usage example that illustrates typical parameter combinations but does not systematically explain each parameter, so baseline 3 is appropriate.

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 renders HTML/CSS to pixel-perfect images, uses a specific verb ('Render'), and distinguishes itself from AI-generation tools by naming the sibling tool canvas_create_image for those cases.

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?

Explicit 'Use when' and 'Do not use when' sections, with direct reference to canvas_create_image for AI-generated imagery. Provides clear context and exclusion criteria.

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