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PatchDesign.AI

Price a custom patch

quote_patch
Read-onlyIdempotent

Price a custom patch from the live PatchDesign.AI production price table: type, size and quantity in, the per-patch and total price in USD out, with the next quantity breaks and what the price already includes (artwork, a pre-production sample, worldwide shipping). Quantity 1 returns the single-patch (sample) prices. Use it when the user asks about a price or the minimum quantity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
widthInNoWidth in inches, 1 to 12.5. Default 3.
heightInNoHeight in inches, 1 to 12.5. Default 3.
quantityNoHow many patches. Default 100. Use 1 for a single patch.
patchTypeNoPatch type: embroidered (default), woven, chenille, printed, pvc-2d or pvc-3d. Iron-on, velcro and sew-on are backings on an embroidered patch, so use embroidered for those.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real context: pricing is read live from the production table, the response includes per-patch price, total, next quantity breaks, and what the price covers (artwork, pre-production sample, worldwide shipping), plus the quantity-1 sample-price special case.

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

Conciseness4/5

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

Front-loaded with the core verb+resource, and the rest is dense, non-redundant detail about output and inclusions. The middle clause listing inputs and outputs runs long, but every element 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?

With no output schema, the description carries the return-value burden and handles it well, explaining the shape of the price response and the quantity-1 special case. It stops short of noting failure modes (e.g., unsupported size/type combinations) or table-staleness, which would round it out.

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 description coverage is 100%, so the schema already documents units, ranges, defaults, and the enum (including the iron-on/velcro/sew-on backing note). The description only restates the input dimensions and the quantity-1 case, which the schema also notes; baseline 3 applies.

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?

States a specific verb and resource ('Price a custom patch') and names the data source ('the live PatchDesign.AI production price table'). The input/output contract is spelled out (type, size and quantity in; per-patch and total USD out), which cleanly separates it from design_patch, edit_patch, and order_link.

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

Usage Guidelines4/5

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

Gives an explicit trigger: 'Use it when the user asks about a price or the minimum quantity.' No sibling is named as an alternative and no when-not-to-use condition is stated, but the sibling set (design/edit/order/link) is far enough away that the omission is minor.

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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