Skill UI

A comprehensive framework for establishing governance standards across Notion integrations. It enforces naming conventions for bots, manages page sharing policies to prevent data leaks, validates database schemas (e.g., required property naming, date formats), and provides access audit scripts. Ideal for maintaining consistency and security in large, multi-team Notion environments.

This guide details how to scaffold complete, structured exercise directory setups, including mandatory sections for problems, reference solutions, and conceptual explainers. It outlines precise naming conventions, required files (like readme.md and main.ts), and a robust workflow that ensures the setup passes linting checks. It is ideal for creating new course modules, generating exercise stubs, or structuring large-scale educational curricula.

Generate production-ready images for SEO: OG/social previews, blog heroes, schema images, product photos, infographics, and more. Uses Gemini via nanobanana-mcp, with aspect ratios, resolutions, and domain modes optimized for each use case. Includes post-generation SEO checklist for alt text, file naming, WebP conversion, schema markup, and OG meta tags.

This comprehensive guide provides expert knowledge on setting up, optimizing, and auditing digital analytics tracking. It covers best practices for implementing tracking in GA4, Google Tag Manager (GTM), and utilizing UTM parameters. Users learn how to structure events, define naming conventions (Object-Action), measure conversions, and establish a data-driven approach for marketing and product decisions.

A comprehensive guide for designing and implementing robust Infrastructure as Code (IaC) using Terraform or OpenTofu. Covers module hierarchy design, best practices for naming conventions, structuring multi-environment pipelines, advanced testing strategies (native tests, Terratest, static analysis), and integrating security scanning (trivy, checkov) into CI/CD workflows.

This guide establishes the Conventional Branch specification for naming Git branches. It defines standardized prefixes (e.g., feature/, bugfix/, hotfix/) and enforces strict rules (lowercase, kebab-case, no underscores) to ensure consistency across development teams. Use it to validate, create, or understand the correct naming structure for any new branch, improving project traceability and collaboration.

An interactive workflow for auditing and standardizing naming conventions (tables, columns, measures) in Power BI semantic models (TMDL). It ensures names are human-readable, consistent, and aligned with core business terminology, addressing technical issues like abbreviations, mixed casing, and inappropriate technical prefixes.

A comprehensive guide and playbook for managing feature flags across services or teams. It covers flag taxonomy (Release, Experiment, Ops, Permission), naming conventions, safe rollout strategies, creation checklists, and cleanup policies to prevent technical debt. Ideal for standardizing feature flag practices and governance.

This skill performs a comprehensive audit of Figma component libraries. It checks for naming inconsistencies, component coverage gaps, variant completeness, and overall design system health. The output provides a structured report with prioritized issues, actionable naming conventions, and a step-by-step fix plan, ensuring design consistency across products.

This skill guides the deployment of decoy files, or "canary tokens," across critical file systems. These files act as tripwires, monitoring for unauthorized changes (modification, deletion, renaming). By tracking these high-value decoys, systems can detect ransomware encryption activity in real-time, providing a low false-positive, high-fidelity detection layer that complements traditional EDR and backup solutions.

Create magazine-style visual notes that turn a concept into a narrative dossier: problem, failed attempts, turning point, insight, and naming. Ideal for education, concept history, and storytelling layouts.

This skill helps developers create highly focused, folder-specific documentation (`CLAUDE.md` and `AGENTS.md`). It systematically analyzes all files in a target directory to extract project purpose, operational constraints, naming conventions, and critical decisions. This deep context ensures that future AI agents (like Claude or Codex) operate with localized knowledge, preventing them from relying on global, generalized instructions and improving their accuracy in that specific domain.