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List ticket followups

glpi_list_followups
Read-onlyIdempotent

List followups (comments) of a ticket, oldest first, with the author's name (user_name).

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)
ticketIdYesItem ID

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

A3.9/5.0
Behavior4/5

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

With the annotations covering read-only, idempotent, and non-destructive behavior, the description adds useful context beyond that: the results come back oldest-first, and each entry includes the author's name. It doesn't discuss pagination or volume limits, but ordering is a genuine behavioral detail that the annotations do not convey.

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?

It is a single sentence with little waste, and it gives the key facts first: what is listed, the order, and the author field. The useful information shows up right away, with no extra padding.

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 output schema exists, so the description does not need to explain return values. For a simple listing tool with annotations and full schema coverage, it covers what an agent needs to call the tool. Only the mention of pagination or when to choose a sibling could be added.

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 percent, so all four parameters are already fully documented in the schema. The description adds no parameter guidance beyond naming user_name as a returned field; it says nothing about range, fields, or format. For this dimension, a score of 3 is the right baseline.

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?

This describes a specific verb and resource: it lists the followups of a specific ticket. The parenthetical '(comments)' plus the note about ordering and the author field adds extra detail, and the sibling tools glpi_list_change_followups and glpi_list_problem_followups make it clear this is the ticket variant.

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 lets you infer that this reads followups for a given ticketId and does not create one; that job belongs to glpi_add_followup. However, it never explicitly says when to use this instead of glpi_list_timeline or glpi_get_ticket, and it does not state any exclusions or prerequisites.

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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