data_html_table

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions the conversion behavior (first row as header) but does not disclose error handling, edge cases, or the exact format of the output (<table> code is vague). The description is minimal and leaves important behavioral traits uncovered for a pure function with no annotations.

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 concise sentence that is front-loaded with the core purpose, followed by input/output specifics. Every word contributes value, and there is no wasted or redundant phrasing.

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?

The tool is simple (3 params, no output schema) and the description covers the essential transformation (CSV/JSON to HTML table) including the header-row rule. It lacks details about return format nuances and error behavior, but given the low complexity and clear core, it is reasonably complete for an agent to select and invoke the tool.

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 67% (data and style have descriptions, data_type only has enum/default). The description adds meaning by clarifying that the data parameter accepts CSV or JSON arrays and that the first row of CSV is treated as a header. It does not explain the data_type parameter explicitly, but the coverage is moderate and the description provides some complementary context.

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 generates HTML table code from CSV or JSON input, with a specific verb ('generates') and resource ('HTML table'). It does not explicitly differentiate from sibling tools like data_html_convert, but the input format and output are clearly specified.

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 implies the primary use case (converting CSV/JSON to an HTML table) but does not explicitly mention when to use this tool over alternatives or when not to use it. There is no mention of exclusions or comparisons to sibling tools, so the guidance is only implied.

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