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List ticket validations

glpi_list_ticket_validations
Read-onlyIdempotent

List approval and validation requests for a GLPI ticket, showing requester, approver, and status so you can track who must approve and whether it was granted or refused.

Instructions

List approval/validation requests for a ticket, with requester and approver names (user_name, validator_name) and status_name in the GLPI user's language (status: 1 = not subject to approval, 2 = waiting, 3 = granted, 4 = refused).

Input Schema

TableJSON 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)
ticketIdYesItem ID

Output Schema

TableJSON 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 observedv3.5.2

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world). The description adds genuine domain context beyond them: the status code legend (1-4) and the fact that status_name is localized to the GLPI user's language. It does not mention pagination via the range parameter, a minor gap.

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?

A single front-loaded sentence that leads with the action and resource before the field/status details. Dense but no wasted words; could be slightly clearer with sentence breaks but earns its place.

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?

An output schema exists so return values needn't be explained, yet the description usefully pre-declares the status enum semantics. For a read-only list tool with full schema coverage, nothing essential is missing beyond usage routing.

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% with two enums, so the schema already documents range, fields, format and ticketId. The field names in the description (user_name, validator_name, status_name) are output fields, not inputs, so the description adds nothing to parameter understanding. Baseline 3 is appropriate.

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+resource ('List approval/validation requests for a ticket') and enumerates the key returned fields (user_name, validator_name, status_name). It clearly reads as the read-only 'list' counterpart to the create/update/delete_ticket_validation siblings, though it never names those siblings explicitly.

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?

The description gives no when-to-use guidance, no prerequisites, and no routing to alternatives such as glpi_create_ticket_validation or glpi_get_ticket. Usage is only implied by the purpose statement itself.

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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