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NestingCalc Calculators

linear_cutting_optimizer

Optimize 1D cutting plans for bars, pipes and profiles (linear cutting stock problem, best-fit decreasing heuristic). Returns bars used, per-bar cut lists with positions, total waste and unplaced parts. A web_url with the plan prefilled is included for a visual SVG diagram.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kerfNoSaw blade width consumed by each cut
trimNoUnusable trim at bar ends
unitYesUnit for all lengths
partsYesParts to cut
stock_countNoHow many stock bars are available
stock_lengthYesLength of one stock bar

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the heuristic (best-fit decreasing), implying non-optimal results, and lists expected outputs (bars used, cut lists, waste, unplaced parts) plus a web_url for visualization. It does not mention potential failure modes like parts exceeding stock length, but covers the core behavioral traits sufficiently.

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?

Two sentences with no redundancy. The first sentence states the purpose and heuristic, the second lists outputs and the web_url. Information is front-loaded and every word earns its place.

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?

Given the tool has 6 parameters and no output schema, the description covers the essential return values (bars used, cut lists, waste, unplaced parts) and the visual aid. It does not explain error handling or edge cases, but those are not critical for a calculator tool. The description is sufficiently complete for an agent to invoke it correctly.

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?

Schema coverage is 100%, so the baseline is 3. The description adds the algorithm context (best-fit decreasing) which indirectly informs how parameters like kerf and trim affect results, but it does not explicitly explain any parameter beyond what the schema already provides. It adds marginal value, consistent with the baseline.

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

Purpose5/5

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

The description clearly states the tool optimizes 1D cutting plans for bars, pipes, and profiles, specifying the resource and the operation. It also names the heuristic (best-fit decreasing), which distinguishes it from the 2D sheet_cutting_optimizer sibling. The purpose is unambiguous and distinct.

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for linear materials but does not explicitly contrast with alternatives like sheet_cutting_optimizer. It mentions the linear cutting stock problem, giving context, but lacks explicit when-to-use or when-not-to-use guidance. An agent would infer the use case from '1D' but not receive direct routing instructions.

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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