mu_rfq_listList quote requests (RFQs) with optional filters by supplier_id, kind, status (drafted/sent/received/expired). RFQs are scoped to your account (admin sees all).
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | ||
| status | No | ||
| supplier_id | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only mentions scoping. It lacks details on side effects, pagination, ordering, or limits, leaving the agent uncertain about behavioral traits.
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?
Two concise sentences with front-loaded action and filters. Every sentence adds value without redundancy.
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?
Covers essential information for a simple list tool, but omits pagination, sorting, response format, and error handling which are relevant for completeness.
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 0%, but description explains all three parameters (supplier_id, kind, status) and their role, including status enum values, compensating well for missing schema descriptions.
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 the verb 'List' and the resource 'RFQs', includes key filters, and distinguishes from sibling tools like mu_rfq_create and mu_rfq_record.
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?
It specifies RFQs are scoped to your account (admin sees all), giving clear context. It could explicitly mention alternatives but still provides enough guidance.
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.