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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds meaningful behavioral details beyond annotations: quantities come from the same engine as the Studio configurator, prices are read live from Shopify, the build grid auto-snaps to 60mm, and the per-market surcharge depends on the `country` parameter. This goes beyond what the annotation alone provides, though it does not mention output structure (covered by output schema) or error handling.

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 exactly two sentences. The first sentence front-loads the verb, resource, and scope; the second adds two important behavioral facts (same engine as configurator, live Shopify prices by country). No filler, no tautology—every word earns its place.

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 16 parameters, the combination of a rich schema, output schema, and annotations already covers most of the burden. The description supplies the overarching context: what the tool computes, where the numbers come from, how pricing varies by market, and the grid snapping behavior. It also offloads template examples to a sibling tool. The tool is fully understood for an agent to select and invoke correctly.

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 is fully self-descriptive (100% coverage) with detailed descriptions for every parameter, including shape-specific fields, layer limits, and country rules. The tool description itself adds little to parameter understanding—it restates the engine and live pricing context but does not need to, because the schema already explains each field thoroughly. Baseline of 3 is appropriate.

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 opens with a specific verb ('Compute') and names the exact resource: bill of materials (panels + connector pins) and total EUR price. It also enumerates the product family (GridGarden modular Brick Premium raised bed rectangle/L/U or freestanding wall) and input dimensions in millimetres, clearly distinguishing it from sibling tools like studio_bom_to_cart (cart operation) or studio_templates_list (templates).

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 clearly implies when to use this tool (to get a quote/BOM from dimensions) and even directs users to studio_templates_list for ready example dimensions in the shape parameter. It does not explicitly state 'use studio_catalog_bricks for product info' or exclude when not to use it, but the context is enough to avoid confusion among siblings.

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