Bill-of-materials cost roll-up for furniture: buy quantity = net qty x (1 + waste%, verified presets: S4S lumber 18%, rough 28%, nested panels 10%, hardware 3%), line and total costs, cost per product and a selling price from a target margin (price = cost / (1 - margin)).
| Name | Required | Description | Default |
|---|---|---|---|
| lines | Yes | ||
| products | No | Products this BOM covers | |
| margin_pct | No | Target margin on selling price, % | |
| labor_per_product | No | Direct labour per product |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It transparently explains the calculation logic for buy quantity, cost outputs, and selling price, and even provides verified waste presets. It does not mention side effects, but as a calculation tool this is sufficient.
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 dense sentence with no filler, front-loading the core purpose and formulas. It is somewhat long and packed, but every clause earns its place by conveying essential costing behavior.
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?
Despite having no output schema and no annotations, the description covers the main outputs (line/total costs, per-product cost, selling price) and the formulas. It is slightly incomplete because it omits the role of labor_per_product and does not explicitly state default behavior, though schema covers defaults.
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 already describes most parameters, so the baseline is 3. The description adds meaningful semantic value by defining the buy-quantity formula, waste presets, and margin-based price formula. However, it does not explain how labor_per_product factors into the cost roll-up.
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 uses a specific verb ('cost roll-up') and names the exact resource ('bill-of-materials ... for furniture'). It includes concrete formulas, which makes the tool's purpose unmistakable and clearly distinguishes it from the sibling measurement/estimation calculators.
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?
Usage context is implied through 'for furniture' and the BOM roll-up wording, but there is no explicit when-to-use guidance or comparison with alternatives such as manufacturing_yield or rough_sizing. No exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.