GLPI MCP Server v2

glpi_get_problem_stats

Fetch detailed statistics for a specific problem by ID to assess resolution progress and metrics.

Instructions

Retorna as estatísticas de um problem.

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": {
      "id": "<id>"
    },
    "name": "glpi_get_problem_stats"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	ID do problem

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 21, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits, but it only says 'returns statistics.' It implies a read operation but does not explicitly state that it is read-only, what statistics are included, how the response is structured, or whether any side effects exist. This is insufficient for a tool with zero annotation support.

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?

The description is a single, front-loaded sentence with no wasted words. It immediately communicates the core action and object. Despite being short, every word contributes to the stated purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a simple one-parameter tool with no output schema, so the description should describe the nature of the returned statistics. However, 'estatísticas de um problem' is ambiguous (e.g., counts, timings, status breakdowns) and does not explain response format or any business context. The description is not complete enough for an agent to confidently use the tool without further guessing.

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?

The input schema has 100% coverage for the sole parameter 'id', described as 'ID do problem'. The description adds no additional parameter-specific meaning beyond what the schema already provides. Per the baseline for high schema coverage, a score of 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?

The description clearly states a verb ('Retorna' / 'returns') and a resource ('estatísticas de um problem'), making it evident the tool retrieves problem statistics rather than the problem record or its timeline. It distinguishes from siblings like glpi_get_problem and glpi_get_problem_timeline through the 'statistics' concept, though it does not explicitly frame it as an alternative to those tools.

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 offers no guidance on when to use this tool versus other problem-related tools. It does not mention conditions, prerequisites, or alternatives. There is only a bare statement of what the tool returns, leaving the agent to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.