Test Reporter MCP Server

get_flaky_tests

Retrieve a list of flaky tests that fail then pass on retry, sorted by flakiness rate, to identify unreliable tests.

Instructions

Get a list of flaky tests (tests that fail then pass on retry) across the project, sorted by flakiness rate. Note: This scans all tests - use smaller 'days' values for faster results.

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_flaky_tests"
  }
}

Input Schema

Name	Required	Description
`days`	No	Days to look back (default: 3). Use smaller values for faster results.
`limit`	No	Maximum results to return (default: 20)
`project_id`	No	Project ID to filter by (optional)
`min_flaky_rate`	No	Minimum flaky rate percentage to include (default: 5)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.0.8Sep 13, 2026

TDQS

A3.5/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses a cost/performance trait (full project scan, smaller windows are faster), but says nothing about permissions, pagination beyond the limit param, or what fields are returned. Partial behavioral disclosure for an annotation-free tool.

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?

Two tight sentences: the core purpose and the flakiness definition come first, followed by the scan-cost caveat. No filler, and the highest-value information is front-loaded.

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

Completeness3/5

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

For a four-parameter, annotation-free list tool with no output schema, the description covers purpose and cost behavior but omits what the returned list actually contains and whether results are paginated or limited by anything besides 'limit'. Adequate but with clear gaps for an agent that needs to interpret the output.

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 all four parameters including defaults and the days tradeoff are already documented in the schema. The description's re-statement of the days hint adds no meaning beyond the schema, so the baseline of 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?

The description states a specific verb and resource ('get a list of flaky tests') and even defines the term ('tests that fail then pass on retry') plus the sort order by flakiness rate. It is clear on its own, but it does not distinguish itself from the nearby sibling get_flaky_specs, which an agent could easily confuse it with.

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?

There is a useful performance hint ('this scans all tests - use smaller days values for faster results'), which is implied usage guidance around the days parameter. However, there is no explicit when-to-use statement and no named alternative among the many siblings (get_flaky_specs, get_test_history, get_failure_patterns), so selection is left to inference.

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

Deploy Server