read_excel_as_table

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

Annotations already declare readOnlyHint=true, so the agent knows it's a safe read operation. The description adds that the output is a compact table (context-efficient) and mentions schema inference, which are useful behavioral traits. But it doesn't disclose output structure details (e.g., how rows are represented, row limits, or error behavior), leaving some behavioral transparency gaps beyond the annotation.

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 only two sentences long. The first sentence states the core function and output format; the second adds a key differentiator (context efficiency) and a feature (schema hints). It is front-loaded and contains no filler or redundant wording.

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's complexity (12 parameters, 0% schema coverage, no output schema), the description is inadequate. It does not explain how to specify source ranges, row/column options, or the meaning of compact and row_mode. An agent cannot correctly configure calls without consulting external documentation or guessing. The description covers only the primary intent and a single advantage, leaving most operational details unspecified.

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 explain the 12 parameters. It only vaguely references 'optional inferred schema hints,' which corresponds to infer_schema, but does not name or explain any other parameter (filepath, sheet_name, start_row, row_mode, etc.). This is a major gap for such a parameter-rich tool; the description fails to compensate for the absent schema documentation.

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: 'Read Excel data as a compact table with headers and rows or record objects.' It identifies the specific resource (Excel data) and output format, and explicitly contrasts with sibling read_data_from_excel ('Much more context-efficient than read_data_from_excel for structured data'), making it distinguishable from that common alternative.

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 provides a clear usage hint: use this tool over read_data_from_excel for structured data when context efficiency matters. It also implies suitability for downstream steps via 'optional inferred schema hints.' However, it does not mention other closely related siblings (e.g., read_excel_table, quick_read) or state when not to use it, so guidance is partial.

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