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QA health report

generate_quality_report
Read-only

Generate a Markdown QA health report summarizing regressions, flaky tests, incidents, performance drift, and pass-rate trends so you can paste results into Slack, Confluence, or Jira.

Instructions

Markdown QA health report: summary, regressions with the commit that introduced them, flaky tests with fixes, environment incidents, performance drift and pass-rate trend. Ready to paste into Slack, Confluence or a Jira comment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description usefully discloses the return artifact's format (Markdown) and section contents, but says nothing about cost, latency, or that it aggregates across runs.

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?

Two front-loaded sentences that lead with format and content, then consumption targets. Every clause is informative, though the contents list is dense enough to verge on enumeration for its own sake.

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 no output schema, the description must describe the return value, and it does so clearly by naming the report's sections. The only real gap is that it never relates to the last_n parameter or explains how the report scopes its data.

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 single parameter last_n has 100% schema description coverage, so the schema fully documents the range constraint. The description never mentions run-scoping at all, so it adds nothing beyond the schema; 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?

A specific verb (generate) and resource (QA health report) with an enumerated list of the report's contents, so an agent knows exactly what it produces. It doesn't distinguish itself from the sibling export_dashboard, which plausibly overlaps as an aggregate-output tool, so it stops short of 5.

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?

'Ready to paste into Slack, Confluence or a Jira comment' implies the intended consumption context, but there is no explicit when-to-use-this vs. the many per-metric siblings (get_pass_rate_trend, find_flaky_tests, detect_regressions) that this report aggregates. Usage is implied rather than stated.

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