Audit Agno AI agent projects across 10 dimensions and generate a scorecard.
npx skills add https://github.com/acardozzo/rx-suite --skill project-agno-rx
Please help me install this Agent Skill. Skill: project-agno-rx Source: https://github.com/acardozzo/rx-suite/tree/main/skills/project-agno-rx Command: npx skills add https://github.com/acardozzo/rx-suite --skill project-agno-rx
This Skill provides a comprehensive, automated audit of Agno AI agent projects, identifying critical gaps and prescribing actionable improvements to ensure world-class quality and adherence to best practices.
Run the project-agno-rx skill to audit the current Agno project for best practices.
High-intent search queries and answers about installing and using this skill.
You can audit an Agno AI agent project by running an automated evaluation across 10 dimensions including agent design, tool integration, RAG, memory, and safety to generate a detailed scorecard and improvement plan.
An Agno agent quality audit includes deep code analysis of agent design, RAG setup, memory management, team coordination, safety, deployment, and testing, producing dimension-specific grades and an overall project score.
Yes, pyright is a required dependency to perform the deep code analysis and evaluate your Agno agent project against best practices.
You evaluate multi-agent team coordination in Agno by running an automated audit that scores your team configuration against framework best practices and provides actionable architectural enhancements.
Yes, auditing your Agno AI agent project can generate architectural diagrams alongside a detailed scorecard to guide your development towards A+ quality.
The best way to identify gaps in Agno RAG setup and memory management is to perform a deep audit that evaluates these dimensions against framework best practices and outputs a prioritized improvement plan.
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