quality-integration-test

Automate Maestro-Flow integration testing with CSV-wave orchestration across L0-L3 layers.

511|63|Updated Mar 17, 2026
One-click install
npx skills add https://github.com/catlog22/Maestro-Flow --skill quality-integration-test
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: quality-integration-test
Source: https://github.com/catlog22/Maestro-Flow/tree/main/.codex/skills/quality-integration-test
Command: npx skills add https://github.com/catlog22/Maestro-Flow --skill quality-integration-test

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a self-iterating integration test cycle that orchestrates CSV-wave pipelines to validate codebases across L0-L3 layers with adaptive strategy to converge on required coverage, replacing ad-hoc QA processes.

Core Features & Use Cases

  • Self-iterating CSV wave-based test cycles across L0-L3, with discoveries, context propagation, and adaptive strategy.
  • Generates per-wave tasks, executes via spawn_agents_on_csv, and aggregates results into master tasks for continuous improvement.
  • Use Case: Run phased validation of a new integration path from code discovery to E2E verification, with reflective iteration until convergence.

Quick Start

Run the auto-enabled integration cycle with default targets to validate the codebase across all layers.

Frequently Asked Questions about quality-integration-test

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate multi-layer integration testing from static analysis to E2E verification?

Multi-layer integration testing is automated through a CSV-wave orchestration pipeline that validates codebases across L0 to L3. It applies a deterministic phase-based approach with adaptive strategy looping to converge on required coverage targets.

What is CSV-wave orchestration for integration testing and how does it work?

CSV-wave orchestration generates per-wave task files and executes them via agent spawning to validate codebases iteratively. Findings and context propagate from each wave into the next, enabling adaptive strategy adjustments until coverage converges.

How do I run self-iterating integration tests with configurable concurrency and coverage targets?

Self-iterating integration tests run in auto mode with configurable concurrency, iterations, and coverage targets. The pipeline generates CSV tasks per wave, orchestrates agents, and aggregates results into master tasks for continuous improvement.

Can I use adaptive strategy looping to converge on integration test coverage for a new code path?

Adaptive strategy looping validates a new integration path from code discovery through E2E verification with reflective iteration. Discoveries from each wave propagate context forward, adjusting the strategy until coverage targets are met.

Does multi-agent orchestration support context propagation from findings across validation waves?

Multi-agent orchestration propagates context from findings across each CSV wave. Agents spawned per-wave execute tasks, and results aggregate into master tasks, feeding discoveries into subsequent waves for continuous strategy refinement.

What are the limitations of phased validation pipelines with auto mode for end-to-end testing?

Phased validation pipelines require codebases suited for L0-L3 layer validation and depend on deterministic phase-based execution. Auto mode assumes default targets are acceptable, and convergence depends on the adaptive strategy's ability to reach coverage goals.