ai-engineering-toolkit

A structured prompt evaluation workflow requires repeatable checklists and guardrails to assess production readiness. This toolkit orchestrates end-to-end AI engineering workflows, applying modular frontmatter-driven design to evaluate and govern AI prompts consistently.

Context budgeting allocates token limits strategically across retrieved documents to optimize RAG design. The toolkit provides structured workflows that define context boundaries, ensuring retrieval-augmented generation systems remain within operational limits and perform reliably.

An agent safety audit systematically checks AI workflows for deployment readiness and security vulnerabilities. This toolkit implements structured safety assessment workflows with guardrails and checklists to govern AI agent behavior and mitigate risks.

Yes, the toolkit supports prompt tuning and deployment governance by providing scalable templates and evaluation frameworks. It turns AI coding assistants into a senior partner, enabling consistent planning and governance across AI projects.