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List orders

swell_list_orders
Read-only

List orders, with MongoDB-style filtering, sorting, search, and expansion. Swell backend REST API: GET /orders.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for pagination (default 1).
sortNoSort expression, e.g. "date_created desc" or "name asc".
limitNoMax records to return (1–1000, Swell default 15).
whereNoMongoDB-style filter as a JSON object string, e.g. {"active":true,"price":{"$gte":10}}.
expandNoComma-separated related fields to expand, e.g. "variants,categories".
searchNoFree-text search across the model's searchable fields.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The readOnlyHint annotation already declares this as a read-only operation. The description goes beyond by specifying supported behaviors (MongoDB-style filtering, sorting, search, expansion) and the exact REST endpoint, giving the agent a solid sense of operational scope. It doesn't discuss pagination limits or return shape, but these are partially covered by schema parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences: the first states the core purpose and features, the second provides the REST endpoint context. No filler or redundancy; every sentence contributes useful information and is front-loaded with the tool's main function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a listing tool with six optional parameters and no output schema, the description sufficiently conveys the tool's role and capabilities. It doesn't explicitly state the return format (a list of orders), but this is strongly implied by the name and the context. The schema covers parameter details, so overall the description is complete enough for effective selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All six parameters (page, sort, limit, where, expand, search) are already fully documented in the schema, including examples. The description's mention of 'filtering, sorting, search, and expansion' mirrors the parameter names without adding extra semantic depth beyond the schema, so it earns the baseline score for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool lists orders and describes key features (MongoDB-style filtering, sorting, search, expansion). The resource is explicit ('orders'), distinguishing it from sibling list tools for other resources (e.g., list_carts, list_products). The underlying REST endpoint (GET /orders) adds further specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The action is clear ('List orders'), so an agent knows when to use this tool: when order listing is needed. However, it doesn't explicitly contrast with alternatives like swell_get_order (for single order retrieval) or swell_query (generic query), so it falls short of full 'when-to-use vs alternatives' guidance.

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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