Get customization options
get_customization_optionsCustomization scope and guidance for one SKU, or the published options across the range when no SKU is given.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| sku | No | Optional product SKU. |
get_customization_optionsCustomization scope and guidance for one SKU, or the published options across the range when no SKU is given.
| Name | Required | Description | Default |
|---|---|---|---|
| sku | No | Optional product SKU. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden, and it does disclose meaningful mode-dependent behavior: a SKU yields scope and guidance for that product, while omitting it yields published options across the range. It stops short of stating that this is a read-only lookup, whether results can be empty, or anything about permissions or rate limits.
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?
A single well-formed sentence that front-loads the primary case and appends the fallback condition. Every clause carries information; there is no filler.
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?
For a zero-required-parameter lookup with no output schema and no annotations, the description covers both invocation paths and what conceptually comes back in each. It could be slightly richer about what 'guidance' and 'published options' actually contain, but nothing needed to call it correctly is missing.
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?
Schema coverage is 100% and the schema already documents the single optional 'sku' parameter, so the baseline is 3. The description earns above baseline by explaining the semantic consequence of omitting the SKU (falls back to range-wide published options), which the schema does not state.
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 names a specific resource (customization scope/options) and clearly splits it into two modes: one SKU vs. range-wide published options. It is distinguishable from siblings like get_product or search_products, though it never explicitly contrasts itself with them.
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 conditional phrasing ('when no SKU is given') implicitly tells the agent which mode applies based on input, which is usable guidance. However, there is no explicit statement of when to reach for this tool versus get_product or compare_products, and no exclusions or prerequisites.
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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