Skip to main content
Glama
SamuelBalbas

tryton-stock-mcp

by SamuelBalbas

get_official_product_quantity

Retrieve the official product quantity for a specified location to audit inventory in Tryton.

Instructions

Read Tryton's contextual product quantity for one location.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idYes
location_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that the tool reads a quantity, without explaining what 'contextual' means, how context is resolved, what quantity form is returned, or any edge cases such as zero or unavailable quantities.

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, front-loaded sentence with no filler. Every word contributes to identifying the operation and the main object of concern.

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 tool is simple with two obvious parameters and an output schema, so a very short description can be acceptable. However, the vagueness of 'contextual product quantity' leaves meaningful gaps about how the quantity is determined and when this tool is the right choice among many similar stock-related siblings.

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

Parameters2/5

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

Schema description coverage is 0%, so the description should compensate, but it adds no parameter semantics beyond what the input schema already shows. The parameter names product_id and location_id are fairly self-explanatory, but the description does not clarify how they map to Tryton's contextual quantity semantics.

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 identifies a read operation ('Read') and specifies the resource: Tryton's contextual product quantity for one location. This distinguishes it from sibling tools like get_product_detail or get_tryton_context, though the meaning of 'contextual' could be more explicit.

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?

No guidance is provided for when to use this tool versus sibling alternatives such as get_product_detail, get_tryton_context, or summarize_product_location_flows. The name implies a direct quantity lookup, but the description does not state conditions, exclusions, or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.