budget_variance_analysis

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

No annotations are provided, so the description carries the full burden. It discloses the key behavioral trait: 'Mutates workbook only if output_file provided.' It also describes the return value shape. This is strong transparency, though it could have also mentioned error conditions or performance implications, but the mutation note is the most critical behavior.

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 appropriately sized, structured into Args, Returns, and Notes sections. Every sentence adds value: the purpose, parameter descriptions, return type, and side-effect note. There is no fluff, and the formatting makes it easy to scan.

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 description is complete for a tool with 7 parameters and no output schema. It covers the operation purpose, all parameter semantics, the return value, and the mutating side effect. No critical information is missing for an AI agent to select and invoke it correctly.

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 coverage is 0% (no descriptions in the schema). The description compensates by listing each parameter with brief meaning: file_path as 'Workbook path', sheet_name as 'Worksheet name', column identifiers as 'Column identifiers for the analysis', header_row as '1-based header row index', and output_file as 'Optional path to write results.' This fully clarifies the purpose of each parameter beyond types and defaults.

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 opens with a specific verb+resource: 'Compare budget vs actual values in a sheet and return variances per category.' This clearly states the tool's function and differentiates it from sibling financial tools like financial_ratio_analysis or dcf_analysis, which address different computations.

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 context ('Compare budget vs actual values in a sheet') but does not explicitly state when to use this tool over alternatives or provide exclusions. It lacks guidance like 'Use when you need variance analysis' or 'Do not use for simple cell reads.' The safety note about mutating the workbook is useful but not usage guidance.

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