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List rule criteria (global)

glpi_list_rule_criteria
Read-onlyIdempotent

List rule criteria via GET /RuleCriteria. Optionally filter by rules_id (works for any rule type: RuleTicket, RuleChange, RuleMailCollector).

Input Schema

NameRequiredDescriptionDefault
rangeNoPagination range, e.g. 0-49
fieldsNoField set: 'essential' (default, trims internal GLPI fields) or 'all'
formatNoOutput format: 'json' (default) or 'markdown' (a table for listings, key/value lines for one item; returned in both the text and the structured result)
rules_idNoRule ID to filter by
expand_dropdownsNoExpand dropdown IDs to names

Output Schema

NameRequiredDescriptionDefault
dataNo
noteNoPagination hint: how to fetch the next page
countNoItems in this page
formatNo'markdown' when data holds the markdown rendering

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is fully covered. The description adds the endpoint and the cross-rule-type scope, but says nothing about pagination behavior, result volume, or default limits beyond what the schema's range/fields params already carry.

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?

Two compact sentences with zero filler, and the core action plus endpoint are front-loaded ahead of the optional filter detail. Nothing can be trimmed without losing information.

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?

With an output schema present, rich annotations, and 100% schema coverage, the description need only establish purpose and scope, which it does. It could be stronger by explicitly naming the rule-type-specific sibling to route the agent, but no essential calling information is missing.

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 all five parameters are already documented in the schema and the baseline is 3. The description adds only one useful nuance beyond the schema: that rules_id filtering spans all rule types, not just RuleTicket.

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 (list rule criteria) and names the underlying endpoint GET /RuleCriteria. The parenthetical that it works for any rule type (RuleTicket, RuleChange, RuleMailCollector) implicitly separates it from the rule-type-specific sibling, but it never names that sibling directly.

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?

It gives the one filtering option (rules_id) and the scope of rule types it covers, which implies when it is the right pick over glpi_list_rule_ticket_criteria. However, there is no explicit when-to-use/when-not statement or named alternative, leaving the routing inference to the agent.

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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