Generates a personalized AB-100 study plan based on the user's self-assessed confidence across the three AB-100 domains, prioritizing weak areas with estimated hours and Microsoft Learn module links. Use when the user asks for a study plan, is unsure what to study, or wants exam prep guidance.
Expert Azure architecture guidance grounded in the Well-Architected Framework and current Microsoft docs. Use for designing new Azure solutions, reviewing existing architectures, service-selection trade-offs across reliability/security/cost/performance/operations, and multi-region or zero-trust topologies.
Use this agent when you need to audit and improve the accessibility of existing markdown documentation, including README files, tutorials, guides, and any .md content. This agent applies GitHub's five accessibility best practices (descriptive links, alt text, heading hierarchy, plain language, list structure) and…
Expert assistant for developing Model Context Protocol (MCP) servers in Python using FastMCP, mcp package, Pydantic, and async patterns. Use when building MCP tools, resources, prompts, or debugging Python MCP server issues.
Author, refactor, validate, and deploy Azure infrastructure as code in Bicep (preferred) and ARM JSON. Use when creating or editing .bicep / .bicepparam files, designing modules, decompiling or migrating ARM templates to Bicep, wiring what-if and deployment-stack workflows, hardening IaC for security (managed…
Build Model Context Protocol (MCP) servers in Python (FastMCP), JavaScript, or TypeScript. Use when creating new MCP servers, adding tools/resources/prompts, configuring transports (stdio/HTTP), or debugging MCP protocol issues. Triggers on requests for MCP development, AI tool creation, or Claude Desktop integration.
Develop and extend the WARNERCO Robotics Schematica system - an agentic RAG application with FastAPI, FastMCP, LangGraph orchestration, and 3-tier memory (JSON/Chroma/Azure AI Search). Use when working on the schematica backend, adding schematics, modifying the LangGraph flow, updating dashboards, or deploying to…
Instructions for timothywarner-org/context-engineering, covering claude.md, working style (tim's preferences), project overview, development commands and warnerco schematica.
MCP server "claudedesktop-warnerco-schematica" as configured in timothywarner-org/context-engineering. Runs locally from the warnerco-mcp Python package. Needs 1 environment variable to run.
AB-900 practice buddy: exam-realistic items + admin scenario walkthroughs, grounded in Microsoft Learn via Microsoft Learn MCP, Context7, and MarkItDown.
Instructions for timothywarner-org/ab900, covering copilot instructions, repository purpose, key locations, skill and agent conventions and grounding and validation rules.
Generate AB-900 practice questions that feel like the real exam without copying it. Every item is grounded in current Microsoft Learn content, uses modern M365 and Purview terminology, and follows Microsoft-style exam item rules (scenario-first, plausible distractors, no trick wording).
Generate realistic 5-10 minute admin scenario walkthroughs through M365 admin centers. Each walkthrough is a guided simulation of a real AB-900 admin task with numbered steps, exact navigation paths, correct settings, and exam relevance notes.
Generates a personalized AB-900 study plan based on the user's self-assessed confidence across the three exam domains, prioritizing weak domains with estimated hours and Microsoft Learn module links.
Instructions for timothywarner-org/az104-cert-buddy, covering copilot instructions, repository purpose, key locations, skill and agent conventions and mcp server ids.
Generate AZ-104 practice questions that feel like the real exam without copying it. Every item is grounded in current Microsoft Learn content, uses modern Azure terminology, and follows Microsoft-style exam item rules (scenario-first, plausible distractors, no trick wording). Use when the user asks for practice…
Create short AZ-104 practice labs (10-20 minutes) that are executable and self-validating. Every lab includes prerequisites, exact tasks, validation steps, expected outputs, and cleanup. Use when the user asks for a hands-on lab, practice exercise, or guided walkthrough.