Skill UI

A comprehensive toolkit for integrating with the official WhatsApp Business Cloud API (Meta). Supports message sending, template management, webhooks (HMAC-SHA256), and advanced customer service automation. Provides ready-to-use boilerplates in Node.js and Python, facilitating scalable and professional communication solutions.

Xberg is a document intelligence library supporting 107 formats including PDF, Office, and images. It extracts text, tables, and metadata using OCR and chunking. Available for Python, Node.js, Rust, and CLI. Ideal for developers building document processing applications with multi-language bindings and structured output.

This skill helps design and build 360-degree feedback systems for businesses. It manages reviewer data, subjects, cycles, visibility, and scoring. Outputs can be generated in CSV, SQL, JSON Schema, or Notion formats. It is suitable for peer reviews and holistic feedback tracking, ensuring structured data collection without drifting artifacts.

This skill manages a register of free design tools, fonts, icons, and templates. It verifies license types, commercial use permissions, attribution rules, export formats, and vendor lock-in risks. It helps businesses vet tools for zero-budget projects, ensuring accessibility and compliance without legal opinions.

Builds a brand asset register for logos, photography, icons and marks, capturing formats, variants, dimensions, rights, licences, and approved uses for brand control.

Turns a long idea, transcript, article, or draft into a Twitter/X thread where every tweet stands alone. It first checks whether a thread is warranted, builds a spine of beats, drafts each tweet, and formats the result with three-dash separators.

Deconstruct a viral short video into hook, beats, and CTA, then rebuild it around your own subject as a shot list, beat frames, and narration using the paid hosted Beatra service.

This skill provides guidance on extracting tabular data from PDFs, spreadsheets, and images using the xberg tool. It covers layout-aware table detection, selection of table models (TATR, SLANet variants), output formats (Markdown or JSON), and known limitations. Useful for processing financial statements, invoices, and scientific tables.

Learn how to configure xberg's --format and --content-format flags to optimize document extraction for different consumers. Covers LLM context, RAG indexing, JSON parsing, and token reduction strategies for efficient data pipelines.