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Use this skill if /track:init is called OR you notice the project contains tracking files (CLAUDE_SOURCES.md or CLAUDE_PROMPTS.md). Automatically tracks research sources and major prompts when enabled. Checks ./.claude/.ref-autotrack marker file for activation status and ./.claude/.ref-config for verbosity settings. Appends to CLAUDE_SOURCES.md (WebSearch/WebFetch) and CLAUDE_PROMPTS.md (major requests) using [User]/[Claude] attribution.
Direct Preference Optimization (DPO) for aligning models with preference data without separate reward models. Triggers: dpo, preference optimization, rlhf, ref_model=none, patchdpotrainer, dpotrainer.
Embed and initialize OpenAI's ChatKit widget in Rails views. Use when adding ChatKit to a page, configuring the openai-chatkit custom element via data attributes, syncing themes with dark/light mode, handling Turbo navigation, or setting up attachment uploads. Triggers on ChatKit embed, openai-chatkit element, chat widget initialization, or theme sync.
Discover available Agent skills. Use when users ask "what skills are available", "list skills", "show me skills", or want to browse installed skill capabilities.
AI-powered unified development orchestrator combining debugging, refactoring, performance optimization, code review, testing integration, and profiling into comprehensive development workflows with Context7 integration, TRUST 5 validation, and enterprise-grade automation
Create new skill for repeatable workflow. Use when user wants reusable skill pattern. Creates .claude/skills/[name]/SKILL.md.
Suite of tools for creating elaborate, multi-component Copilot.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.
Use when building "MCP server", "Model Context Protocol", creating "Claude tools", "MCP tools", or asking about "FastMCP", "MCP SDK", "tool development for LLMs", "external API integration for Claude"
LLM integration patterns for building AI-powered applications with Anthropic Claude and OpenAI APIs. Use when integrating Claude or OpenAI APIs, implementing chat features, adding streaming responses, managing multi-turn conversations, implementing prompt engineering, tracking LLM costs, handling rate limits, or building AI-powered features. Includes client setup, error handling, and cost optimization.
LLM evaluation and prompt optimization with Evidently.ai. Covers text descriptors, dataset metrics, LLM-as-a-Judge patterns, and automated prompt optimization for classification and generation tasks.
AI-powered enterprise Claude Code hooks orchestrator with intelligent automation, predictive maintenance, ML-based optimization, and Context7-enhanced workflow patterns. Use when designing smart hook systems, implementing AI-driven automation, optimizing hook performance with machine learning, or building enterprise-grade workflow orchestration with automated compliance and monitoring.
Guide AI feature development using @monsoft/ai package with Langfuse telemetry. Use when building AI-powered features, text generation, or structured outputs.
Universal execution engine using scientific method to achieve ideal state. USE WHEN complex tasks, multi-step work, "run the algorithm", "use the algorithm", OR any non-trivial request that benefits from structured execution with ISC (Ideal State Criteria) tracking.
AIOS Agent Operating System and Cerebrum SDK for building, deploying, and orchestrating AI agents
Extracts traces, observations, and metrics from Langfuse Cloud (EU) API for debugging, telemetry analysis, and regulatory audit trails. Generates ALCOA+ compliant reports, exports to pandas DataFrame, and supports time-range/user/session filtering. Use when investigating production issues, generating compliance documentation, or analyzing LLM costs and performance. MUST BE USED for pharmaceutical audit trail generation requiring GAMP-5 traceability.
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
