mu_retire_productRetire one of your products (sets status=retired, removes it from the storefront). Owner-only. Requires Authorization: Bearer <api_key>.
| Name | Required | Description | Default |
|---|---|---|---|
| sku | Yes | SKU of the product to retire (must belong to one of your stores). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It reveals the effect (status=retired, removed from storefront) but does not discuss reversibility, side effects, or related data impacts. This is adequate but not rich.
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 two efficient sentences with no wasted words. It front-loads the main action and follows with necessary preconditions.
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?
Given the tool's low complexity (one parameter, no output schema, no annotations), the description is sufficiently complete. It explains purpose, preconditions, and effect, though it lacks detail on return value or error scenarios.
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 parameter sku is fully documented in the schema (100% coverage). The description adds the condition 'must belong to one of your stores', providing extra context beyond the schema description.
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 clearly states that it retires a product by setting its status to 'retired' and removing it from the storefront, using a specific verb and resource. This distinguishes it from siblings like mu_update_product, which likely handles other updates.
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 provides explicit usage conditions: owner-only and requires authorization header. However, it does not mention when not to use this tool or suggest alternatives, such as using mu_update_product for other status changes.
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.
Each tool has a clearly distinct purpose; no two tools appear to do the same thing. Even closely related tools (e.g., mu_quote vs mu_rfq_create, mu_preview_mockup vs mu_create_product) are differentiated by read-only vs. action, or draft vs. send.
Tool names consistently use snake_case with the mu_ prefix, and follow a clear verb_noun or noun_verb pattern. Groups like mu_gi_*, mu_ship_*, mu_rfq_* maintain internal consistency. No arbitrary or ambiguous names.
The tool count of 28 is on the higher side but appropriate for the breadth of functionality (registration, product lifecycle, manufacturing, shipping, sales, admin). It's well within a manageable range for a comprehensive server.
The tool surface covers core workflows comprehensively: registration, product CRUD (with create, update, retire), manufacturing quotes (informational and RFQ with spec drafting), shipping (CSV, tracking, status updates), sales data, and gi-specific management. Minor gaps include lack of store update/delete and product search, but these are not critical for the main use cases.