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 of behavioral disclosure. It mentions 'analyze' and 'variance calculations,' implying a read-only computation, but doesn't specify if it modifies files, requires specific permissions, handles errors, or outputs results in a particular format. For a tool with 4 parameters and no annotations, this leaves significant behavioral gaps, such as whether it's destructive or has rate 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?

The description is a single, efficient sentence: 'Analyze budget vs actual performance with variance calculations.' It's front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity. Every part of the sentence contributes directly to understanding the tool's function.

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 annotations, no output schema, and 4 parameters, the description is incomplete. It doesn't cover behavioral aspects like safety or performance, output format, or error handling. For a data analysis tool with multiple inputs, more context is needed to ensure the agent can use it correctly, such as what the variance calculations entail or how results are returned.

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 100% description coverage, detailing each parameter (e.g., 'filePath' as path to CSV/Excel). The description adds no additional parameter semantics beyond the schema, as it doesn't explain how 'actualColumn' and 'budgetColumn' interact or provide examples. With high schema coverage, the baseline is 3, but the description doesn't compensate with extra insights, so it meets the minimum viable level.

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: 'Analyze budget vs actual performance with variance calculations.' It specifies the verb ('analyze'), resource ('budget vs actual performance'), and method ('variance calculations'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'ratio_analysis' or 'trend_analysis,' which might also involve financial comparisons, so it misses full 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a data file), exclusions, or comparisons to siblings like 'correlation_analysis' or 'statistical_analysis' that might handle similar data. Without any context on usage scenarios or alternatives, the agent lacks direction for selection.

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