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Lightspeed Retail (X-Series) MCP by usefulapi

List stock orders (consignments)

lightspeedxseries_list_consignments
Read-only

List consignments: supplier stock orders (type SUPPLIER), transfers between outlets (OUTLET), stocktakes (STOCKTAKE) and returns (RETURN), with status (OPEN, SENT, DISPATCHED, RECEIVED, STOCKTAKE_*, CLOSED, CANCELLED), outlet, supplier, due and received dates, totals. Paginate with next_after. GET /consignments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoSUPPLIER = purchase / stock orders.
afterNoCursor: only records with a version number greater than this. Omit for the first page; then pass next_after from the previous call. Stop when data is empty.
beforeNoOnly records with a version number up to this (rarely needed).
statusNo
outlet_idNoOnly consignments of this outlet.
page_sizeNoRecords per page (the vendor default applies when omitted; 50-100 keeps replies short).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

The readOnlyHint annotation already covers safety, so the description adds useful behavioral detail by explaining the pagination cursor (next_after) and the returned dimensions (outlet, supplier, due/received dates, totals). It does not cover rate limits or response envelope details, but it exceeds the annotation baseline.

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 a single dense but front-loaded passage with no filler. The core purpose, type/status enumerations, pagination hint, and endpoint are all packed efficiently.

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 read-only list tool with no output schema, the description provides enough context: what is listed, what filters exist, what fields are returned, and how to paginate. It lacks explicit sibling differentiation, but otherwise an agent has what it needs to call the tool correctly.

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

Parameters4/5

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

Schema coverage is high (83%), but the description adds meaningful semantics beyond the raw enum labels: it maps SUPPLIER to supplier stock orders, OUTLET to transfers between outlets, and clarifies the status groups. It does not add much for after/before/page_size beyond what the schema already provides.

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

Purpose4/5

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

The description clearly states a specific verb and resource: it lists consignments and enumerates the four subtypes (SUPPLIER, OUTLET, STOCKTAKE, RETURN). It implicitly distinguishes itself from get_consignment by being a list operation, but it does not explicitly name siblings or contrast with list_consignment_products.

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

Usage Guidelines3/5

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

The description gives filtering context (type, status, outlet, supplier, dates) but never explicitly states when to use this tool versus get_consignment or list_consignment_products. Usage is implied by the listing/filtering language rather than stated as 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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