QA Copilot MCP Server

List flaky tests across multiple runs

list_flaky_tests

Compare multiple Playwright JSON reports to detect flaky tests that pass in some runs but fail or time out in others.

Instructions

Compares the same tests across two or more Playwright JSON reports (e.g. the last N CI runs of the same suite) and returns every test whose outcome wasn't consistent - it passed in some runs and failed/timed out in others.

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": {
      "reportJsons": "<reportJsons>"
    },
    "name": "list_flaky_tests"
  }
}

Input Schema

Name	Required	Description	Default
`reportJsons`	Yes	Two or more Playwright JSON reporter outputs, oldest first, as raw strings.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 24, 2026

TDQS

A4.2/5.0

Behavior3/5

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

With no annotations available, the description correctly conveys that this is a read-only comparison and what task qualifies as flaky. However, it does not disclose how missing tests across reports are treated, whether the result is influenced by report ordering beyond the schema note, or what fields are returned per test — leaving some behavioral details implied rather than explicit.

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?

One tight sentence that states the operation, the input shape, the example use, and the result. There is no filler, and the purpose appears immediately. It is concise despite the long sentence because every clause adds new information.

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?

For a single-parameter query tool with no output schema, the description explains the input to the comparison, what counts as 'flaky', and what the output represents. It omits edge-case details, such as how test records without entries in all reports are handled or the exact shape of each returned test, but the overall information is sufficient for an agent to invoke it correctly for a typical flaky-test scenario.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents reportJsons as raw Playwright JSON reporter outputs, oldest first, with minItems=2 (100% schema coverage). The description adds the meaningful context that these should be 'the last N CI runs of the same suite', which clarifies the intended input beyond the bare schema definition.

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?

The description opens with a specific verb-resource pair ('Compares the same tests across two or more Playwright JSON reports') and explicitly names the result ('returns every test whose outcome wasn't consistent'). It clearly differentiates this from siblings like get_repo_ci_status or explain_failure by focusing on flaky test detection across multiple runs.

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?

The description provides contextual use ('two or more... e.g. the last N CI runs of the same suite') and makes the minimum-input condition explicit. It does not spell out 'when not to use' or name alternatives, but the multi-report scope plus sibling tool context makes the boundary reasonably clear.

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

Deploy Server