Document Zolai AI architecture, data pipelines, and model definitions.
npx skills add https://github.com/peterlianpi/zolai-ai --skill zolai-project
Please help me install this Agent Skill. Skill: zolai-project Source: https://github.com/peterlianpi/zolai-ai/tree/main/website/zolai-project/.cursor/skills/mir-project Command: npx skills add https://github.com/peterlianpi/zolai-ai --skill zolai-project
This project context provides a centralized architectural blueprint and governance for building the Zolai AI Second Brain, enabling planning of data pipelines, language models, and cross-cutting tooling.
Review the project context and plan a feature roadmap using the architecture, data pipelines, and LLM tooling described here.
High-intent search queries and answers about installing and using this skill.
To plan data pipelines for an AI second brain architecture, you need a centralized blueprint that coordinates dataset workflows, model definitions, and cross-team governance artifacts like AGENTS.md to ensure structural alignment.
AI project architecture governance for LLM fine-tuning includes stack component references, agent-role indexes, and project documentation that coordinate dataset workflows and model training tasks across multiple teams.
Yes, you can use this architecture to plan feature roadmaps for a Bible corpus and linguistics wiki, as it provides specific data pipelines and model definitions tailored for these specialized linguistic datasets.
You coordinate cross-team collaboration for dataset workflows and risk governance by applying a centralized architectural blueprint that defines agent roles, stack components, and governance artifacts to align all teams.
Yes, you need comprehensive governance documentation such as AGENTS.md to manage AI training dashboard pipelines, ensuring that all feature roadmaps and dataset workflows align with the defined project stack.
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