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Azure Cost Optimization Workflow

az-cost-optimize

github/awesome-copilot

Analyzes IaC files and live Azure resources to validate SKUs, usage, and costs, then generates GitHub issues (one per recommendation plus an EPIC) so teams can track implementation of prioritized savings.

Microsoft Copilot Agent Kit

declarative-agents

github/awesome-copilot

Provides an end-to-end kit for building Microsoft 365 Copilot declarative agents across basic, enterprise, and validation workflows, with TypeSpec definitions, JSON schema validation, and Agents Toolkit integration for planning, testing, deployment, and optimization.

Fabric Lakehouse Guide

fabric-lakehouse

github/awesome-copilot

Explains Fabric Lakehouse storage, data organization, security, shortcuts, and optimization practices so you can design, build, and monitor Lakehouse solutions leveraging Microsoft Fabric best practices.

Multi-Stage Dockerfile Best Practices

multi-stage-dockerfile

github/awesome-copilot

This guide provides comprehensive best practices for creating optimized, secure, and efficient multi-stage Dockerfiles. Learn how to separate build environments (builder stage) from minimal runtime environments, significantly reducing image size and attack surface. Topics covered include layer caching optimization, security hardening (non-root users), and using minimal base images for reproducible builds.

PostgreSQL Optimization Assistant

postgresql-optimization

github/awesome-copilot

Assistant for PostgreSQL developers that highlights native features, advanced data types, performance tuning patterns, and extension usage to optimize queries, indexes, and analytics in PostgreSQL projects.

Power BI DAX Optimizer

power-bi-dax-optimization

github/awesome-copilot

Guides a Power BI DAX expert through performance, readability, best-practice, and maintainability reviews; recommends variable reuse, context tuning, and error handling; then outputs an optimized formula plus justification for analytics models.

Power BI Data Model Design Review

power-bi-model-design-review

github/awesome-copilot

A comprehensive expert prompt for evaluating Power BI data models. It guides the assessment of model architecture (Star Schema, relationships), storage optimization (Import, DirectQuery, Dual), data quality, performance scalability, and governance best practices. Use this when reviewing an existing BI model to ensure it is robust, maintainable, and highly performant.

Power BI Performance Triage

power-bi-performance-troubleshooting

github/awesome-copilot

Provides systematic Power BI performance troubleshooting guidance covering model optimization, DAX design, report layout, and capacity diagnostics, plus tool-driven measurement tips for faster page loads, interactions, and query execution.

SEO Optimization Playbook

affaan-m/everything-claude-code

Audits crawlability, metadata, structured data, Core Web Vitals, and content signals while planning keyword mapping, internal linking, and sitemap fixes so teams can steadily boost organic visibility.

Content Quality and SEO Audit

sickn33/antigravity-awesome-skills

Provides a comprehensive audit of content quality, focusing on E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) signals, readability, and structural integrity. Use this tool when reviewing content for SEO optimization, assessing academic citation readiness, or ensuring adherence to modern search engine and AI best practices.

Single Page SEO Deep Analyzer

sickn33/antigravity-awesome-skills

Perform a comprehensive, deep-dive audit on a single URL, covering all critical aspects of Search Engine Optimization. Analysis includes on-page elements (title, headings, meta tags), content quality (readability, E-E-A-T), technical structure (schema, canonical, OG tags), image optimization, and core web vitals potential issues. Ideal for SEO audits and content quality checks.

Generate Code Session Usage Reports

anthropics/claude-plugins-official

Analyzes and generates a self-contained, explorable HTML report detailing usage metrics for Claude Code sessions. It tracks token consumption (input/output), subagent usage, skill calls, and cache efficiency across specified time ranges. This tool helps developers visualize resource waste and pinpoint areas for workflow optimization, ensuring cost-effective and efficient AI development cycles.

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