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List ticket followups

glpi_list_followups
Read-onlyIdempotent

List a GLPI ticket's followups (comments), oldest first, with author names to review the full conversation history.

Instructions

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

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

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description does add one genuine behavioral fact — results are ordered 'oldest first' — and notes that the author's name (user_name) is included, but says nothing about pagination defaults or volume.

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?

A single sentence with zero filler, front-loading the resource and appending the ordering guarantee where it is most useful.

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 and full annotation coverage, the description only needs to add what structured fields don't convey. Ordering and the presence of user_name do that; only pagination/volume context is missing, which is a minor gap.

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 range, fields and format are already fully documented in the schema; the description adds nothing about parameters. Baseline 3 applies.

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 followups (comments) of a ticket') and disambiguates the term with the synonym 'comments'. The ticket scope implicitly separates it from glpi_list_change_followups and glpi_list_problem_followups, though it never names those siblings.

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 or when-not-to-use guidance, and no alternatives are mentioned (e.g. glpi_list_timeline or glpi_get_ticket, which could also surface followups). Usage is only inferable from the name.

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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