create_table

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

With no annotations, the description carries the burden of behavioral disclosure. It explains the generated artifact (grid-based table, auto-sized columns) and the return value (absolute path to a .excalidraw file), but it does not disclose file-system side effects such as overwriting behavior or what happens when output_path is omitted.

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 compact and well-structured: a clear one-line purpose, a short behavior/use-case paragraph, an Args block, and a Returns line. Every sentence adds information, and the most important facts are front-loaded.

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?

For a moderately parameterized creation tool with no annotations, the description covers purpose, behavior, parameters, and return format. It does not specify constraints like row/header length alignment or allowed color/theme values, but the essential information an agent needs to make a basic correct call is present.

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 0%, so the description must compensate. It provides one-line explanations for all six parameters, notably clarifying that rows is 'a list of rows, each row is a list of cell values' and identifying title and output_path as optional. It remains vague on accepted values for header_color and theme, but it covers every parameter with useful meaning.

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 opens with a specific verb and resource: 'Create a table diagram,' and then elaborates with concrete details (grid-based table, header row, data rows) and use cases like comparison tables and feature matrices. This clearly distinguishes it from sibling diagram-generation tools.

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 states clear contexts where this tool is appropriate: 'Great for comparison tables, feature matrices, and data displays.' It does not explicitly exclude alternatives or list when-not-to-use scenarios, but the use-case framing gives an agent enough context to select it over other diagram tools.

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