Explore skills

ML/AI health IT safety assessment for Digital Clinical Safety Officers. Applies NHS Digital's supplementary guidance for Assurance of Machine Learning in Autonomous Systems (AMLAS healthcare) alongside DCB0129/DCB0160. Covers ML component identification, training data bias, model performance, explainability, failure modes, and MHRA regulatory considerations. Use when a health IT system includes AI

Clinical Safety Case Report (CSCR) writer for health IT systems. Produces a structured safety case argument aligned with NHS England DCB0129/DCB0160 requirements. Covers system description, intended purpose, hazard summary, risk control evidence, the safety argument, and DCSO sign-off sections. Use when preparing for Clinical Authority to Release (CATR) or demonstrating compliance.

Ship a CQAI tool to GitHub and Hugging Face Spaces in a single workflow. Runs pre-flight checks, commits and pushes to GitHub, pushes to HF Spaces, waits for build, and verifies the app is live. Use after /qa-streamlit passes.

Frame the value of an AI feature in terms of user outcomes and business impact, not model capabilities. Use this skill when a team needs to articulate why an AI feature is worth building and what success looks like.

Design and run a structured evaluation of an AI prototype to assess quality, user experience, and readiness for development. Use this skill when an AI feature prototype needs to be evaluated before committing to full development.

Develop a structured business case for a product investment including ROI, costs, risks, and expected outcomes. Use this skill when a team needs to justify a product investment to leadership or stakeholders.

Model customer lifetime value (LTV) and customer acquisition cost (CAC) to assess unit economics and growth sustainability. Use this skill when a team needs to understand whether the business model is economically sustainable.

Build and compare forecasting scenarios to support product and business planning decisions. Use this skill when a team needs to project outcomes under different assumptions.

Analyze churn patterns, identify root causes, and design retention intervention strategies. Use this skill when a team needs to understand why customers are leaving and how to stop it.

Design a retention playbook with interventions for at-risk accounts, expansion opportunities, and churn prevention tactics. Use this skill when a CS team needs structured plays for proactively improving retention.

Design and operate a Voice of Customer program that surfaces systematic insights from customers. Use this skill when a team needs a structured system for collecting and acting on customer feedback.

Structure a product dashboard that supports consistent, fast decision-making. Use this skill when a team needs to design or improve a product metrics dashboard.