Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman:compress or "compress memory…
Ultra-compressed communication mode. Cuts token usage 75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or…
Guidelines for creating formula-driven Excel workbooks with xlsxwriter. Inject live Excel formulas with cached values so workbooks display immediately and recalculate when actuaries change selections. Covers formula patterns, cross-workbook references, and shared formatting modules.
Guide for improving GitHub Copilot Agent performance through skills, custom instructions, AGENTS.md, or other configuration. Use this when asked to improve agent behavior, create/update skills, modify custom instructions, update AGENTS.md, or customize GitHub Copilot performance in repositories.
Instructions for cas-team-analyst/team-analyst, covering claude.md — teamanalyst, readme is a product artifact, project overview, file structure and what owns what and single source of truth files — edit these directly.
Framework AI LDF selector for chain-ladder reserving across all measures. Applies structured decision framework with documented criteria. Invoke once to make LDF selections for all measures (Paid Loss, Incurred Loss, Reported Count, etc.) in the analysis.
Open-ended AI LDF selector for chain-ladder reserving across all measures. Makes selections using actuarial judgment and pattern recognition without a rigid rules framework. Invoke once to make LDF selections for all measures (Paid Loss, Incurred Loss, Reported Count, etc.) in the analysis.
Framework AI tail curve selector for chain-ladder reserving across all measures. Applies a phased tail curve decision framework with required documentation for ASOP 43 compliance. Invoke once to make tail curve selections for all measures in the analysis.
Open-ended AI tail curve selector using holistic actuarial judgment and pattern recognition across all measures. Makes independent tail curve selections based on curve diagnostics, triangle characteristics, and experience without rigid rule sequencing. Invoke once for all measures in the analysis.
Framework AI selector for ultimate losses and counts by accident year. Applies structured framework to weight Chain Ladder, BF, Cape Cod, Berquist-Sherman, Frequency-Severity, Benktander, and related methods based on maturity, diagnostics, and data conditions. Makes one selection for Loss (choosing between…
Open-ended AI selector for ultimate losses and counts by accident year. Makes selections using actuarial judgment and pattern recognition without a rigid rules framework. Provides creative second opinion alongside framework selector by holistically weighing method indications. Makes one selection for Loss (choosing…