consultancy-practices

The consultancy-practices skill provides a structured framework for AI agents to operate as expert quality engineering consultants. It is designed for engineers, leads, and architects who need to assess, transform, or provide ongoing advisory services for software projects. By following a proven methodology—Listen, Discover, Prioritize, Transfer, and Measure—the agent can systematically diagnose bottlenecks in testing, deployment, and development lifecycles.

• Perform comprehensive codebase assessments and generate executive-ready reports on quality scores, technical debt, and test coverage.
• Facilitate ROI-based decision making for quality initiatives, allowing teams to justify testing investments to stakeholders.
• Coordinate fleet-based operations, leveraging agents like qe-quality-analyzer and qe-regression-risk-analyzer to provide multi-faceted insights.
• Bridge the gap between 'what clients say' (e.g., 'we need automation') and 'what they mean' (e.g., 'feedback is too slow'), enabling more accurate and effective recommendations.
• Implement strategic transformations by moving teams away from manual gatekeeping toward developer-owned quality and risk-based testing strategies.

Usage notes include always starting with deep discovery—asking targeted questions about recent deployments and production bug histories to understand the true context. The skill integrates seamlessly with the broader agentic-qe fleet to handle specific tasks like security scanning, performance analysis, and flaky test stabilization. Input requirements typically involve access to project directories or existing CI/CD telemetry. Outputs include prioritized recommendation roadmaps, quantitative ROI analyses, and suggested team-wide quality practices. The skill enforces a core consulting philosophy: empower the client team to succeed independently rather than creating long-term dependency on the agent. It is highly effective for crisis management (e.g., fixing blocking production issues) and long-term quality transformations (3-12 months). Always track success against metrics defined at the start of the engagement.