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break_even_analysis

Calculate break-even units and revenue from fixed and variable costs and price per unit, showing the sales volume needed to cover costs.

Instructions

Calculate break-even units and revenue given fixed and variable costs.

Args: fixed_costs: Total fixed costs. price_per_unit: Selling price per unit. variable_cost_per_unit: Variable cost per unit.

Returns: dict: break_even_units and break_even_revenue.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fixed_costsYes
price_per_unitYes
variable_cost_per_unitYes
Behavior3/5

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 describes the return dict and inputs, but it does not mention potential errors (e.g., division by zero if price <= variable cost) or explicitly state that this is a pure calculation with no side effects. The behavior is implied by 'Calculate' but not fully transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a single-purpose opening sentence followed by standard Args/Returns documentation. No wasted words, and the format is easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple calculation tool, the description covers the essentials: inputs, output, and core formula. The absence of an output schema is compensated by the explicit return dict description. However, it does not mention edge cases like the requirement that price exceed variable cost, leaving a minor gap in completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds one-line definitions for each parameter ('Total fixed costs', 'Selling price per unit', 'Variable cost per unit'), which marginally supplements the schema titles. Since the schema description coverage is 0%, this is helpful but not extensive. The return dict explanation is useful, though it pertains to output, not parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Calculate break-even units and revenue given fixed and variable costs.' It uses a specific verb and resource, making the purpose unambiguous. However, it does not explicitly distinguish itself from sibling financial tools like dcf_analysis or financial_ratio_analysis, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 or any prerequisites. It simply states what it does without mentioning any exclusions or comparison to other tools. No conditions or context for use are given.

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

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