How does this skill help with AI-specific risks?

The skill includes specialized risk patterns specifically for AI/ML projects, covering areas like model drift, training data quality, bias, and LLM hallucinations.

What is the difference between a risk and an assumption in this framework?

A risk is a potential event that might go wrong (probability x impact), while an assumption is something believed to be true that requires validation to prevent it from becoming a risk later.

Can I use this for non-AI software projects?

Absolutely. While it has advanced features for AI, it is a comprehensive risk management tool suitable for any agile software development lifecycle.

How are risks prioritized within the skill?

Risks are scored using a probability and impact matrix, ranging from Low to Critical, which dictates whether a risk requires immediate escalation or simple monitoring.

Agile Risk Management

Name: Agile Risk Management
Author: nsalvacao

bynsalvacao

0•

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Manages project risks, assumptions, clarifications, and dependencies to ensure stable and predictable software delivery cycles.

The Agile Risk Management skill provides a structured, production-grade framework for identifying and tracking the four pillars of project stability: Risks, Assumptions, Clarifications, and Dependencies (RACD). It enables Claude to maintain a living risk register, score impacts using a standardized matrix, and define clear mitigation strategies. Beyond traditional project management, this skill includes specialized patterns for AI/ML-specific risks—such as model drift, data bias, and hallucination—ensuring that modern AI projects remain compliant, reliable, and on schedule.

主な機能

01Assumption validation tracking to prevent deferred risks from stalling projects.

02Automated risk scoring based on probability and impact matrices.

03Standardized RACD registers for risks, assumptions, clarifications, and dependencies.

040 GitHub stars

05Escalation-ready clarification logs for tracking blocking decisions and due dates.

06Specialized AI/ML risk assessment patterns for model drift and data quality.

ユースケース

01Managing AI-specific challenges like model hallucinations or data bias in machine learning workflows.

02Conducting risk assessments during sprint planning or project gate reviews.

03Documenting and validating technical assumptions during the discovery phase of a project.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nsalvacao/nsalvacao-claude-code-plugins risk-management

For use in Claude.ai and ChatGPT

主な機能

01Assumption validation tracking to prevent deferred risks from stalling projects.

02Automated risk scoring based on probability and impact matrices.

03Standardized RACD registers for risks, assumptions, clarifications, and dependencies.

040 GitHub stars

05Escalation-ready clarification logs for tracking blocking decisions and due dates.

06Specialized AI/ML risk assessment patterns for model drift and data quality.

ユースケース

01Managing AI-specific challenges like model hallucinations or data bias in machine learning workflows.

02Conducting risk assessments during sprint planning or project gate reviews.

03Documenting and validating technical assumptions during the discovery phase of a project.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nsalvacao/nsalvacao-claude-code-plugins risk-management

For use in Claude.ai and ChatGPT