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naveen-bitrise

Bitrise Insights MCP Server

bitrise-insights-get-flaky-tests

Retrieve flaky test data from Bitrise Insights, including test cases and detailed execution info such as build IDs, durations, and commit hashes to identify unstable tests.

Instructions

Get comprehensive flaky tests data from Bitrise Insights including test cases and detailed test execution information: build IDs, run durations, pass/fail status, timestamps, branches, stacks, and commit hashes. Uses browser session authentication - a browser window will open automatically when login is required (specialized for flaky test analysis)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_slugNoThe Bitrise app slug (optional, for app-specific results)
durationNoDuration or specific time (e.g., "july", "last week", "P6M")P6M
intervalNoTime interval (hourly, daily, weekly, monthly)monthly
specific_testNoSpecific test to get comprehensive test run details for
workspace_slugYesThe Bitrise workspace slug
include_test_casesNoWhether to include detailed test cases for each app

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly warns that a browser window will open automatically when login is required, a critical side effect an agent must anticipate. It does not mention read-only semantics or rate limits, but the 'Get' verb implies a query and the authentication note is the most material behavior to disclose.

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, well-structured sentence that front-loads the tool's purpose before adding the authentication caveat. Every phrase earns its place: data scope and auth behavior are both essential for correct invocation. There is no filler, redundancy, or excessive detail.

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 tool with no output schema and no annotations, the description supplies key missing context: the exact data fields returned and the interactive authentication requirement. It does not detail the output shape, but the parameter schema covers input semantics. The overall context is sufficient for an agent to call it correctly.

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 the schema already documents all six parameters. The description only loosely aligns with parameters via 'test cases' and 'test execution information', but it does not clarify the specific_test object or include_test_cases flags beyond the schema. The baseline of 3 is appropriate since the description adds little parameter-level meaning.

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 states 'Get comprehensive flaky tests data from Bitrise Insights' with a specific verb and resource, and enumerates concrete data fields (build IDs, run durations, pass/fail status, timestamps, branches, stacks, commit hashes). The phrase 'specialized for flaky test analysis' further distinguishes it from generic insights tools. No siblings are present, so no comparison is required.

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 does not explicitly name alternatives or exclusion criteria, but it clearly establishes the use case: flaky test analysis on Bitrise Insights. The 'specialized for flaky test analysis' phrase gives a clear context for when to invoke this tool. Since no sibling tools are provided, this level of guidance is sufficient.

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

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