read_data_from_excel

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

Annotations already declare readOnlyHint=true, and the description adds valuable behavioral context beyond that: it mentions cursor continuation tokens for range reads, auto-expansion of end_cell, and the compact and values_only modes that alter the response structure. This is useful, non-contradictory information.

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 well-structured: a brief one-sentence purpose, a bulleted Args list, and a Returns section. It covers all parameters without redundancy or fluff, making it both comprehensive and scannable.

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 tool with 10 parameters and no output schema, the description adequately covers all parameters and the return type, including the values_only mode. It could be more explicit about cursor pagination usage (e.g., whether to resend all parameters), but it provides sufficient context for understanding the tool's behavior.

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?

The input schema has zero description coverage (0%), so the description fully compensates by explaining all 10 parameters with concise, meaningful one-liners covering defaults, optionality, and behavior. This is essential for correctly invoking the tool with such a large parameter set.

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 data from an Excel worksheet with cell metadata including validation rules, which is a specific verb+resource+scope. However, it does not explicitly differentiate from sibling tools like read_excel_as_table or quick_read, relying on the metadata mention as an implicit distinction.

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?

There is no explicit guidance on when to use this tool versus alternatives. The description lists parameters but does not state use cases, prerequisites, or alternative tool recommendations, leaving the agent to infer usage context from the tool's name and parameter details.

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