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ohneben's Wafeq MCP

wafeq_units_of_measure_create

Create a new unit of measure for your Wafeq catalog. Specify a name and optional Arabic name, and set whether it is active.

Instructions

๐ŸŸก WRITE ยท creates data ยท Unit Of Measures ยท POST /units-of-measure/

Create unit of measure

Endpoint for creating a new unit of measure.

Not idempotent โ€” calling twice creates two records. Pass idempotency_key (or let the server generate one) to make a retry safe.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesA ModelSerializer that takes additional arguments for "fields", "omit" and "expand" in order to control which fields are displayed, and whether to replace simple values with complex, nested serializations
idempotency_keyNoOptional idempotency key (sent as the X-Wafeq-Idempotency-Key header). A UUID v4 is generated automatically when omitted, so an automatic network retry can never duplicate this operation. Pass your own stable value to make a deliberate re-invocation safe as well.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.0.0

TDQS

B3.3/5.0
Behavior4/5

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

The description adds meaningful behavioral context beyond the annotations: it explicitly says 'Not idempotent โ€” calling twice creates two records' and explains how idempotency_key makes retries safe. This is consistent with the idempotentHint=false and readOnlyHint=false annotations, with no contradiction.

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

Conciseness3/5

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

The header is compact and informative, but the description repeats the same idea: 'Create unit of measure' and 'Endpoint for creating a new unit of measure' are redundant. It could be tighter without losing meaning.

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

Completeness3/5

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

The description covers the endpoint, creation behavior, and idempotency, but there is no output schema and no mention of what a successful response returns. It also does not clarify the relationship to wafeq_item_units_of_measure_create, which leaves an ambiguity an agent might need to resolve.

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?

Schema description coverage is 100%, so the schema already documents body fields and idempotency_key in detail. The tool description's mention of idempotency_key adds little beyond what the schema already states, and no additional parameter-level meaning is provided.

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 states a specific verb and resource: 'Create unit of measure' with endpoint POST /units-of-measure/. It is clear about the action but does not explicitly differentiate this from the sibling wafeq_item_units_of_measure_create, which is also a 'create' tool for units of measure.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives such as wafeq_item_units_of_measure_create or wafeq_units_of_measure_update. It only states that it creates a unit of measure, leaving the selection logic largely 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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