wals.pro AI 4 weclapp

Get reference data

get_reference_data

Read-onlyIdempotent

Fetch one reference entity collection (payment methods, users, etc.) or the combined sales bundle.

Supplies the IDs to plug into quotation / party / task payloads. reference_type="user" serves task-assignee userId values (for the identity acting behind this connection call get_acting_identity instead). reference_type="salesBundle" returns several sales reference types at once (currencies, units, payment methods, payment terms, sales stages, shipment methods, sales channels) plus inferred tenant defaults in one call. For payload building, follow with get_schema(entity) and preview_write_entity.

Args: reference_type: "salesBundle" or a type in REFERENCE_ENTITY_ALLOWLIST (e.g. "currency", "unit", "user", "paymentMethod", "termOfPayment", "shipmentMethod", "ticketStatus", "salesChannel", "salutation", "title", "personRole"). Unknown types fail closed with a static redirect where available. salesChannel returns the tenant's active channels as {key, name} rows — the names behind the NET1/GROSS1/... keys on party/order records. customAttributeDefinition: compact definitions for customAttributes payloads. partyRating is a schema enum — call get_schema('party') instead. Static enums like salutation return source="static_enum" without a weclapp round-trip. limit: Max entries. Defaults to 100 (single type) or 20 rows per collection (salesBundle). With entity, omit it: all matches (up to 300) come back. entity: customAttributeDefinition only — one record type, e.g. "article". name: Case-insensitive "contains" filter on entry names.

Returns: Dict with "results" (single type; cached ~10 minutes) and optionally "resource_uri". salesBundle instead returns one key per collection, "service_article_candidates", "responsible_users", "tenant_defaults" (inferred default IDs) and "notes".

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	No
`limit`	No
`entity`	No
`correlation_id`	No
`reference_type`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 27, 2026

addedInput schema / properties / name

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Name"
+}

Changed1 schema field changedSep 25, 2026

addedInput schema / properties / entity

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Entity"
+}

First observedSep 25, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations cover safety (readOnly, idempotent, non-destructive), but the description adds behavior they cannot convey: ~10-minute caching, fail-closed handling of unknown types, static enums returned without a weclapp round-trip, per-mode limit defaults (100 / 20 / 300), and the shape of the salesBundle response.

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

Conciseness4/5

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

Front-loaded with the core purpose before the Args/Returns breakdown, and nearly every sentence adds operational detail. It is long and the allowlist enumeration plus nested parentheticals make it dense, but the length is defensible for a polymorphic tool with five parameters and zero schema coverage.

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

Completeness5/5

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

An output schema exists, yet the description still sketches the return shape ("results", resource_uri, per-collection keys, tenant_defaults, notes), which helps the agent plan downstream calls. Given the polymorphic reference_type and 0% schema coverage, the behavioral and routing detail is complete apart from correlation_id.

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 description coverage is 0%, so the description carries full burden and largely delivers: reference_type gets an allowlist, examples, and per-value caveats; limit gets mode-specific defaults; entity gets a usage restriction; name gets a case-insensitive 'contains' semantic. The gap is correlation_id, which is never mentioned anywhere.

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?

Names a specific verb (fetch) and resource (reference entity collection) and explicitly scopes the two modes: single type vs. the combined salesBundle. It also distinguishes itself from siblings, telling the agent that get_acting_identity serves the identity case and get_schema('party') serves partyRating.

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

Usage Guidelines5/5

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

States the downstream purpose ("supplies the IDs to plug into quotation / party / task payloads") and gives explicit alternatives with conditions: use get_acting_identity for the acting identity, get_schema for partyRating, and follow with get_schema(entity) and preview_write_entity for payload building. Nothing is left to inference.

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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