Carnegie Quality Strategy is an AI agent skill published by agensi that configures an agent to act as a Software Quality Director for a given codebase. It follows a four-step workflow: repository inspection, maturity assessment, Carnegie principle mapping, and strategy generation.
During the inspection phase, the skill analyzes dependency manifests, CI/CD pipeline configurations, existing test suites, and high-risk code areas such as authentication and payment flows. This produces a Product Understanding Report that grounds all subsequent recommendations in specific file paths, frameworks, and identified gaps rather than generic advice.
The maturity assessment categorizes the project on a scale from Level 0 to Level 5, so the resulting plan is calibrated to the actual state of the codebase rather than an idealized baseline. The skill then maps twenty Carnegie human-centered principles to the findings, producing recommendations that address both technical debt and engineering culture, including stakeholder engagement guidance.
The final output is a quality-strategy.md file covering test engineering, defect management, and a 30-60-90 day execution plan. This document is structured for presentation to CTOs or Engineering Managers. The skill is appropriate when a team needs a written, evidence-based quality strategy rather than ad-hoc testing advice. It is not a runtime testing tool and does not execute tests or modify code directly.