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The most comprehensive Claude Code setup — 29 skills, 9 plugins, 13 hooks, 8 agents, 8 commands. Self-documenting, self-improving, CLI-first. Includes self-interview prompt for personalization.

The most comprehensive Claude Code setup — 29 skills, 9 plugins, 13 hooks, 8 agents, 8 commands. Self-documenting, self-improving, CLI-first. Includes self-interview prompt for personalization.

The most comprehensive Claude Code setup — 29 skills, 9 plugins, 13 hooks, 8 agents, 8 commands. Self-documenting, self-improving, CLI-first. Includes self-interview prompt for personalization.

Use when Claude Code is explicitly inside the Claws Temple Bounty 2.0 path and needs to route between Task 1 to Task 5 in branded Chinese or English. Do not use this for generic numbered tasks or unrelated bounty flows.

Use when OpenCode is explicitly inside the Claws Temple Bounty 2.0 path and needs to route between Task 1 to Task 5 in branded Chinese or English. Do not use this for generic numbered tasks or unrelated bounty flows.

Clinical Risk Management Plan (CRMP) creator for health IT systems. Produces a structured CRMP aligned with NHS England DCB0129/DCB0160 and the NHS Digital CRMP template. Covers scope, safety roles, risk management activities, tools and methods, documentation requirements, and review schedule.

Interactive clinical safety hazard log creator and reviewer. Walks through FMEA-based hazard identification for health IT systems, producing a structured hazard log aligned with NHS DCB0129/DCB0160 templates and the clinical risk matrix (Severity × Likelihood). Use when starting a hazard log, reviewing an existing one, or identifying new hazards after a system change.

Define the success metrics for an AI feature covering quality, user experience, business impact, and safety. Use this skill when an AI feature needs a complete metric framework before launch.

Design workflows that appropriately balance AI automation with human oversight and intervention. Use this skill when a team is building an AI feature and needs to decide when and how humans stay in the loop.

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 product direction review from a UK nursing perspective. The CQAI equivalent of /plan-ceo-review — asks the hard clinical questions before any technical planning. Reviews NMC Standards alignment, patient safety classification, health equity impact, and the "Ward Test". Use this INSTEAD of /plan-ceo-review for any nursing or clinical tool.

QA testing for Streamlit applications — locally or on Hugging Face Spaces. Covers app startup, UI rendering, Streamlit-specific checks (session state, widgets, forms, caching), clinical content accuracy, HF Spaces compatibility, and accessibility. Produces a structured QA report with PASS/FAIL/PARTIAL status.