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Create ticket rule

glpi_create_rule_ticket

Creates a new GLPI ticket business rule with match logic (AND/OR), active status, subtype, and ranking to automate ticket handling.

Instructions

Create a new ticket business rule. Fields: name, match (AND/OR), is_active, sub_type, ranking, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesRule fields

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
replayedNoTrue when an identical recent create was returned instead of repeated

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.5.2

TDQS

B3.1/5.0
Behavior2/5

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

Annotations already convey that this is a non-idempotent, non-readonly, non-destructive creation, so the safety profile is covered. The description adds nothing behavioral beyond that: no mention of permission requirements, validation failures, or the required follow-up steps. With annotations carrying the basics, additional context is what's missing.

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?

Two compact sentences with the action front-loaded and the field list as supporting detail; no filler. The trailing 'etc.' is slightly evasive but costs little.

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?

An output schema exists, so return values need not be explained. For a create tool with an opaque nested object, however, the description omits prerequisites, auth, and lifecycle context (criteria/actions), leaving it only minimally sufficient.

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?

The schema is a bare free-form 'input' object (additionalProperties: {}), so the nominal 100% coverage tells the agent almost nothing. The description compensates by naming concrete fields (name, match with AND/OR values, is_active, sub_type, ranking), which is real added value, though 'etc.' leaves the remaining fields unspecified.

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?

States a specific verb and resource ('Create a new ticket business rule') and the field list sharpens what kind of rule it is. It does not explicitly distinguish itself from the closely related glpi_create_rule_criteria / glpi_create_rule_action siblings, so a 4 rather than a 5.

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?

There is no when-to-use guidance, no prerequisites (e.g. that criteria/actions must be added afterward to make the rule functional), and no reference to the list/get rule siblings. The agent must infer everything from the name alone.

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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