Skip to main content
Glama
Sign In
qa-metrics-mcp

qa-metrics-mcp

by Misfit1982
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Failure clusters

get_failure_clusters
Read-only

Group test failures by normalized root-cause signature and classify each cluster as environment outage, persistent defect, intermittent, or one-off to start root-cause analysis.

Instructions

Group failures by normalized root-cause signature (numbers, ids and quoted values stripped) and classify each cluster: environment outage, persistent defect, intermittent, or one-off. Useful as the starting point for an RCA.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_failure_clusters"
  }
}

Input Schema

NameRequiredDescriptionDefault
runNoLimit to one run (default: all runs in window): run id, build number, commit prefix, 'latest' or 'previous'
last_nNoOnly consider the most recent N runs (default: all runs)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already establish that this is a read-only, closed-world operation. The description adds meaningful behavioral detail beyond annotations: how failures are normalized and which root-cause classes are assigned, though it does not describe the exact return structure or limits.

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 two sentences, front-loaded with the tool's core action and followed by a direct RCA usage note. Every sentence carries useful information with no repetition or filler.

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?

Given the read-only annotations and fully documented parameters, the description is largely complete for an analytical grouping tool. It explains the clustering method and classification categories, though with no output schema it could have said more about the returned cluster structure.

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% description coverage for both parameters, including accepted values for `run` and the default behavior. The description adds no parameter-specific syntax or semantic detail beyond what the schema already provides, so the baseline 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 uses a specific verb, "Group failures," and clearly defines the resource and method: normalized root-cause signatures with four classification categories. It is distinguishable from generic summary or regression tools, though it does not explicitly name sibling tools to differentiate itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context by calling itself "the starting point for an RCA," which tells an agent when this tool is appropriate. It does not include explicit exclusions or name alternative sibling tools, so it falls short of the top score.

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

Deploy Server

Other Tools