List approved RFQs matched to the authenticated supplier. Requires a supplier API key.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| summary | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly, idempotent, non-destructive), the description adds that a supplier API key is required and that only approved RFQs are returned. This is useful behavioral context about authentication and filtering.
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 short, front-loaded sentences with no filler. Every word adds value, and the structure is easy to scan.
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 simple single-parameter tool, strong annotations, and existing output schema, the description is mostly complete. It covers authentication and scope; only minor details like pagination behavior could be added, but they are not essential.
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 schema has zero description coverage, and the tool description does not explain the 'limit' parameter. Even though limit is common, the description fails to compensate for the lack of schema descriptions, leaving the agent to infer behavior from the parameter name alone.
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 tool lists approved RFQs matched to the authenticated supplier. It uses a specific verb ('list'), identifies the resource (RFQs), and specifies scope ('approved' and 'matched to the authenticated supplier'), distinguishing it from related tools like get_supplier_rfq.
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 implies usage context: this is for suppliers retrieving their own approved RFQs, and it notes the requirement of a supplier API key. It does not explicitly name alternatives or when-not-to-use, but the context is clear enough.
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.
Every tool targets a distinct resource, role, or action. For example, list_orders versus list_supplier_orders clearly separates buyer and supplier views, and update_supplier_order versus update_supplier_order_issue versus update_supplier_order_return handle different concerns despite similar names. Rich descriptions eliminate ambiguity.
All tool names consistently use snake_case with a verb_noun pattern (e.g., create_project, list_orders, update_supplier_capabilities, search_products). The style is uniform across reads, writes, lists, and searches, making the API predictable.
With 55 tools, the server far exceeds the typical well-scoped range of 3-15. Even for a broad supply chain platform, 50+ tools hits the rubric's 'extreme mismatch' threshold. The domain is comprehensive, but the sheer number overwhelms and likely complicates agent tool selection.
The tool surface covers the full lifecycle from project creation, BOM management, sourcing, quoting, planning, checkout handoff, orders, returns, issues, warranties, catalog updates, supplier profiles, and validation. It handles buyer and supplier sides with appropriate state transitions, and includes meta tools for connection and schema guidance. No obvious critical gaps exist.