What types of AI models are supported?

The skill classifies and provides guidance for classical ML models, deep learning, LLM integrations, GenAI pipelines (RAG/Agents), and data-only pipelines.

How does this skill help with AI governance?

It enforces the creation of model cards at Gate D and ensures bias assessments and safety evaluations are performed before deployment.

What is the AI Lifecycle skill for Claude Code?

It is a specialized capability that provides domain-specific guidance for AI and ML projects, covering everything from experiment design to production drift monitoring.

Can this skill help with model monitoring after deployment?

Absolutely. It provides instructions for configuring input drift monitoring, latency tracking, and setting up retraining triggers for production models.

Does this skill support LLM and Generative AI projects?

Yes, it includes specific workflows for prompt engineering, hallucination management, and mandatory red-teaming for LLM-based applications.

AI Lifecycle Management

Name: AI Lifecycle Management
Author: nsalvacao

bynsalvacao

0•

数据科学与机器学习

Standardizes AI/ML delivery with end-to-end guidance on experiment design, model validation, and governance for production-grade AI.

The AI Lifecycle skill for Claude Code provides a structured framework for managing the unique requirements of AI and Machine Learning projects within a software delivery pipeline. It operationalizes critical activities that standard software delivery often overlooks, including time-boxed experiment design, rigorous model card generation, bias and fairness assessments, and LLM-specific red-teaming. By integrating these steps into the development workflow, the skill ensures that AI components are justifiable, safe, and continuously monitored for performance and drift from initial hypothesis through to production operations.

主要功能

01Automated model card generation for AI governance and Gate D compliance

020 GitHub stars

03Specialized LLM red-teaming and prompt engineering lifecycles

04Comprehensive AI validation for bias, fairness, and safety assessment

05Pre-configured monitoring setup for model drift and performance metrics

06Structured experiment design with hypothesis tracking and success metrics

使用场景

01Executing mandatory red-teaming and safety checks for GenAI and LLM integrations

02Setting up production monitoring for model drift and automated retraining triggers

03Designing and logging time-boxed ML experiments to prevent research scope creep

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nsalvacao/nsalvacao-claude-code-plugins ai-lifecycle

For use in Claude.ai and ChatGPT

主要功能

01Automated model card generation for AI governance and Gate D compliance

020 GitHub stars

03Specialized LLM red-teaming and prompt engineering lifecycles

04Comprehensive AI validation for bias, fairness, and safety assessment

05Pre-configured monitoring setup for model drift and performance metrics

06Structured experiment design with hypothesis tracking and success metrics

使用场景

01Executing mandatory red-teaming and safety checks for GenAI and LLM integrations

02Setting up production monitoring for model drift and automated retraining triggers

03Designing and logging time-boxed ML experiments to prevent research scope creep

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nsalvacao/nsalvacao-claude-code-plugins ai-lifecycle

For use in Claude.ai and ChatGPT