Statute Analysis Rafal Fryc

Master skill for legal teams using Claude. Loads the right reference for the user's question (privilege configuration, MCP hardening, verification, long documents, practice-area patterns, skill authoring) and routes to specialized starter skills (NDA triage, version diff, meeting brief, citation verification, status synthesis). Auto-invokes when the user mentions legal work, contracts, redlines, NDAs, privilege, attorney-client, court filings, depositions, regulatory compliance, or asks how to set up Claude for a law firm or in-house legal team.

Prepare an organisation for regulatory inspection by assessing readiness against agency-specific focus areas (FDA, EMA, MHRA). Covers warning letter and 483 theme analysis, mock inspection protocols, document bundle preparation, inspection logistics, and response template creation. Use when a regulatory inspection has been announced or is anticipated, when a periodic self-assessment is due, when new systems have been implemented since the last inspection, or after a significant audit finding that may attract regulatory attention.

Design and operate a data integrity monitoring programme based on ALCOA+ principles. Covers detective controls, audit trail review schedules, anomaly detection patterns (off-hours activity, sequential modifications, bulk changes), metrics dashboards, investigation triggers, and escalation matrix definition. Use when establishing a data integrity monitoring programme for GxP systems, preparing for inspections where data integrity is a focus area, after a data integrity incident requiring enhanced monitoring, or when implementing MHRA, WHO, or PIC/S guidance.

Investigate root causes and manage CAPAs (Corrective and Preventive Actions) for compliance deviations. Covers investigation method selection (5-Why, fishbone, fault tree), structured root cause analysis, corrective vs preventive action design, effectiveness verification, and trend analysis. Use when an audit finding requires a CAPA, when a deviation or incident occurs in a validated system, when a regulatory observation needs a formal response, when a data integrity anomaly requires investigation, or when recurring issues suggest a systemic root cause.

Domain knowledge for the Evolution Engine — LLM-powered autonomous strategy discovery from raw OHLCV data. Covers the generate-backtest-select-evolve loop, vectorized backtesting, out-of-sample validation, and strategy graduation. Use when discovering trading patterns, running backtests, evolving strategies, or reviewing evolution logs. Triggers on "evolve", "discover patterns", "backtest", "evolution", "strategy generation", "candidate strategy".

Manage context-mode GitHub issues, PRs, releases, and marketing with parallel subagent army. Orchestrates 10-20 dynamic agents per task. Use when triaging issues, reviewing PRs, releasing versions, writing LinkedIn posts, announcing releases, fixing bugs, merging contributions, validating ENV vars, testing adapters, or syncing branches.