Agent Skills Hub

using-sdlc-engineering

CMMI-based SDLC router providing process guidance, requirements management, architectural decision support, quality assurance, and governance for GitHub and Azure DevOps workflows.

stop

Gracefully pause or close sessions: harvest context, archive work, verify features, and settle AtlasCoin bounties. Use when finishing for the day or wrapping up tasks.

image-fetcher

Fetch, download, and batch process web images in various formats (JPG, PNG, WebP, SVG, etc.) for embedding, archiving, or chat integration.

markitdown

Convert diverse file formats like PDFs, Office docs, images, audio, and web content into clean Markdown, specifically optimized for LLM ingestion, RAG pipelines, and automated text analysis workflows.

frontend-accessibility-best-practices

Accessibility best practices and patterns for React applications to ensure WCAG compliance, semantic structure, and inclusive user experiences.

sast-idor

Automated detection of IDOR vulnerabilities using a three-phase subagent workflow to verify authorization and ownership checks on sensitive endpoints.

tdd-workflow

A rigorous TDD workflow agent that enforces test-first development, ensuring 80%+ code coverage across unit, integration, and E2E tests for features, bug fixes, and refactoring.

kirby-forms-and-frontend-actions

Implements frontend forms and actions in Kirby CMS, including contact forms, file uploads, email handling, and page creation from the frontend.

lading-optimize-submit

Automates the submission workflow for lading performance optimizations, including branch management, git commits, and PR creation.

recipe-finding

Finds recipes via web search and provides a systematic workflow for scaling ingredient portions, handling fractional measurements, and formatting final outputs.

markdown-token-optimizer

Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.

upstash-vector-db-skills

Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.