create_sensitivity_table

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

With no annotations provided, the description carries the full burden. It explicitly discloses that the tool mutates the workbook by inserting a table and warns about overwrite semantics when output overlaps data, which is valuable behavioral context.

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 with Args, Returns, and Notes sections. It is front-loaded with the main purpose and each sentence provides useful information without redundancy.

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 has 8 parameters, no output schema, and no annotations, the description covers the essential aspects: purpose, parameter semantics, return summary, and mutation warning. It could be more explicit about the output cell placement or provide an example, but it is largely complete.

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 compensates by providing concise explanations for each parameter (e.g., 'Cell that contains or references the expression to evaluate'). It clarifies the role of var1/var2 and the expression, adding meaning beyond the raw schema.

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 it creates a 1- or 2-variable sensitivity table, with a specific verb and resource. It distinguishes from siblings like goal_seek or run_solver by focusing on sensitivity analysis over value grids.

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 usage (when you need a sensitivity table) but does not explicitly state when to use this tool versus alternatives or provide exclusions. No clear guidance on selection against sibling tools is given.

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