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Found 6 Skills
AI-native tutor and onboarding workflow for the four independent Claude certification tracks in AI Engineering from Scratch. Use when a learner wants to choose a Claude certification, prepare for CCAO-F, CCDV-F, CCAR-F, or CCAR-P, resume a certification path, learn the next lesson interactively, run and verify practical labs, build scored artifacts, take a diagnostic or mock exam, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.
Data engineering, machine learning, AI, and MLOps. From data pipelines to production ML systems and LLM applications.
Standards for writing/modifying skills—evaluation criteria for density, structure, trigger terms, flexibility, and validation loops.
Deterministic AI engineering workflow with multi-agent teams. Triggers: architect mode, consistency sweep, pipeline audit, team workflow
Design composable agentic primitives for flexible workflows. Use when creating reusable workflow building blocks, designing SDLC primitives, or building agent operations that can be combined in different ways.
Focused interactive tutor for the Model Context Protocol (MCP) path in AI Engineering from Scratch. Start or resume this route when a learner wants to build, secure, debug, verify, or operate MCP clients, servers, transports, gateways, registries, or conformance gates. Teaches one lesson per invocation and records wire evidence in MCP-LEARNING.md.