Review, validate, or create Azure Quickstart Templates following the Azure/azure-quickstart-templates contribution guide. Covers file structure, naming, Bicep/JSON authoring, metadata, README, parameters, best practices, and CI validation rules.
Report bugs in the Content Developer tooling to the development team. Generates structured bug reports with system info, repro steps, and expected/actual behavior. Creates ADO Bug work items with proper routing and parent linking.
Orchestrate Azure documentation workflows — create ADO work items with auto-calculated fields, generate git branch names and commit messages, create PR descriptions with AB# linking, calculate publish dates, and close work items. Replaces the Content Developer MCP server tools with portable skill instructions.
Scaffold and write production-ready Azure documentation articles (how-to, concept, quickstart, tutorial, overview). Generates frontmatter, article structure, and content following Microsoft Learn writing standards.
Editorial quality workflows for Azure documentation — SEO optimization, metadata generation, engagement analysis, markdown auto-fix, sensitive identifier replacement, and link validation. Replicates DocuMentor extension capabilities for use in agent mode or without the extension.
First-time setup for Azure documentation workflows. Guides authentication with Azure CLI and GitHub CLI, configures Git with correct noreply email, and clones documentation repositories with efficient shallow clones. Use when setting up a new machine or onboarding a new content developer.
Verify technical accuracy of Azure documentation using official Microsoft sources. Offers seven workflows: quick in-place fact-check, full standalone report, internal-source verification, freshness review, deep agent-driven check, research-only investigation, and customer incident analysis. All workflows use a tiered source authority hierarchy prioritizing learn.microsoft.com.
Analyze how Microsoft Learn content is chunked and surfaced by the Learn MCP server. Accepts a search query or a direct article URL. Returns a structured report showing how chunks are sized and bounded, how relevant each chunk is to the query, what content is duplicated or missing, and concrete recommendations for improving article structure to produce better RAG retrieval results.