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GIMS Automation MCP Server

by gelarm

create_method_parameter

Create input or output parameters for datasource type methods. Specify whether the parameter is passed when calling the method or returned as a dict key.

Instructions

Create input or output parameter for a datasource type method. Input parameters (input_type=true) are passed when calling the method. Output parameters (input_type=false) are returned as dict from the method.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelYesParameter label - variable name in method code (snake_case, English)
is_hiddenNoIs hidden
method_idYesMethod ID
input_typeNotrue = INPUT parameter (passed to method), false = OUTPUT parameter (returned from method as dict key)
descriptionNoDescription
default_valueNoDefault value
value_type_idYesValue type ID (use list_value_types). IMPORTANT: Do NOT use 'Список' or 'Справочник' types - use 'Объект' instead
default_dict_value_idNoDefault dictionary value ID (for dictionary properties)
Behavior2/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It mostly paraphrases the input_type schema property and does not reveal side effects, prerequisites (e.g., existing method), or return behavior. The description adds no new behavioral context beyond what the input schema already documents.

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 sentences with zero waste, front-loading the verb and object. It efficiently communicates the core distinction between input and output parameters.

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?

The tool is straightforward, and the schema provides complete parameter details. The description covers the essential input/output behavior. It could mention prerequisites like the method_id needing to reference an existing method, but overall the combination of description and schema is sufficient for a create operation.

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 coverage is 100%, so the baseline is 3. The description does not add meaning beyond the schema; it repeats the input_type semantics already defined in the parameter description. The important value_type_id note is present in the schema, not the description.

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?

The description clearly states the tool creates input or output parameters for a datasource type method, distinguishing the two parameter types. This specific verb-resource pairing separates it from sibling tools like create_datasource_type_method or create_datasource_type_property.

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 explains when to use input_type=true vs false, giving functional context for parameter creation. However, it does not explicitly mention alternatives or exclude cases (e.g., use update_method_parameter for modifications), so usage guidance is implied rather than explicit.

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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