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AI & LLM

LLM integrations, prompt engineering, and AI orchestration

7,400 Skills

Unit-aware computation with Pint - convert units, dimensional analysis, unit arithmetic

Planning agent that creates implementation plans and handoffs from conversation context

Identify failure modes before they occur using structured risk analysis

Formal theorem proving with research, testing, and verification phases

Code quality checks, formatting, and metrics via qlty CLI

Query the memory system for relevant learnings from past sessions

Code refactoring workflow - analyze → plan → implement → review → validate

Release preparation workflow - security audit → E2E tests → review → changelog → docs

Store a learning, pattern, or decision in the memory system for future recall

Analyze repository structure, patterns, conventions, and documentation for understanding a new codebase

Use RepoPrompt CLI for token-efficient codebase exploration

Research agent for external documentation, best practices, and library APIs via MCP tools

Document codebase as-is with thoughts directory for historical context

Resume work from handoff document with context analysis and validation

Comprehensive code review workflow - parallel specialized reviews → synthesis