NexTool MCP for GLPI

Create rule criteria

glpi_create_rule_criteria

Add a new criterion to an existing GLPI rule using its rules_id, field, condition, and pattern to define when the rule triggers.

Instructions

Create a new criteria for a rule. Fields: rules_id, criteria (field name), condition, pattern.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "input": "<input>"
    },
    "name": "glpi_create_rule_criteria"
  }
}

Input Schema

Name	Required	Description	Default
`input`	Yes	Criteria fields (rules_id, criteria, condition, pattern)

Output Schema

Name	Required	Description	Default
`data`	No
`replayed`	No	True when an identical recent create was returned instead of repeated

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.5.2Oct 5, 2026

TDQS

C2.9/5.0

Behavior2/5

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

Annotations already declare this is a non-read-only, non-idempotent, non-destructive, closed-world write, so the safety profile is covered structurally. The description adds nothing beyond that: it does not say whether criteria can be duplicated, whether condition/pattern values are validated, or what a duplicate create does (relevant since idempotentHint=false).

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 short sentences, purpose first, field list second, with no filler. It is tight, though the field list largely duplicates the schema's own description rather than adding new information.

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, and annotations carry the mutation semantics. However, for a nested write against an existing rule, the absence of any prerequisite or rule-type constraint leaves the definition only minimally complete.

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 reported at 100%, but the schema itself is a generic wrapper with additionalProperties={} whose only documentation is the same field list. The description does add one genuine clarification, "criteria (field name)", which disambiguates an otherwise confusing parameter name. No detail is given on legal condition operators or pattern formats, so this is baseline-plus.

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 gives a specific verb+resource ("Create a new criteria for a rule") and enumerates the fields involved, so the agent knows exactly what is being created. It stops short of distinguishing itself from close siblings such as glpi_create_rule_action or glpi_create_rule_ticket, which share the same rule-criteria family.

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 statement of when to use this tool, nor any prerequisite (an existing rule id, a valid condition value, or the rule type the criteria must match). The agent must infer the workflow entirely from the name and the sibling list.

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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