read_excel_as_table

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

Annotations already indicate read-only, and the description adds behavioral context: output as a compact table, support for row or record objects, and optional inferred schema hints. This goes beyond the annotation by describing return format and context-efficiency, though it doesn't detail edge cases or limits.

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?

Two concise sentences, front-loaded with the core purpose and followed by a comparative and a qualifier. No wasted words.

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 no output schema and many parameters, the description covers the essential purpose, output format, and a key differentiator. It could be more complete by mentioning range parameters, but the core usage for an agent is sufficiently clear.

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?

With zero schema description coverage, the description partially compensates by hinting at key parameters: 'compact' (compact), 'headers and rows or record objects' (include_headers, row_mode), and 'inferred schema hints' (infer_schema). However, many of the 11 parameters remain unexplained, so it provides only moderate value.

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 reads Excel data as a compact table with headers and rows or record objects. It uses a specific verb ('Read') and resource ('Excel data'), and explicitly distinguishes itself from read_data_from_excel by highlighting context efficiency, satisfying sibling differentiation.

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 explicitly recommends this tool over read_data_from_excel for structured data, giving a clear alternative and condition. This tells the agent when to select this tool, meeting the 'when/when-not' requirement.

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