Skill UI

This skill is designed to enhance the reading efficiency of AI-generated text, such as responses from large language models. It utilizes Rapid Serial Visual Presentation (RSVP) combined with Spritz-style Optimal Reading Pace (ORP) highlighting. By employing this method, users can significantly increase their reading speed to over 600 WPM, allowing for rapid consumption and comprehension of vast amounts of digital text.

This comprehensive dashboard tracks and analyzes usage metrics for AI coding assistants (Cursor) in enterprise environments. It monitors total requests, model consumption, user adoption rates, and associated costs. Managers can use it to optimize resource quotas, control AI spending, and calculate the Return on Investment (ROI) to justify AI tool adoption.

This comprehensive workflow automates the entire post-meeting cycle. It enhances raw transcripts by structuring notes, extracting action items, and summarizing key decisions using advanced AI models. Users can then seamlessly share these structured notes to integrations like Slack, Notion, and CRMs (HubSpot), while also using the Chat feature to draft follow-up emails and automatically update contact records in the built-in CRM.

This guide provides a comprehensive strategy for managing and reducing expenses within the Lindy AI platform. Learn how to audit agent credit consumption, right-size models by using less expensive versions for simple tasks, consolidate redundant agents, and optimize trigger frequency. Implementing these steps ensures cost efficiency and sustainable operation of your AI workflows.

This comprehensive workflow automates the entire meeting documentation process. It handles live or recorded audio input, performing accurate transcription with speaker diarization. Subsequently, it leverages advanced AI models to generate detailed summaries, extract key action items, draft follow-up emails, and create structured meeting minutes, significantly enhancing organizational knowledge retention and operational efficiency.

Provides comprehensive observability for the TwinMind AI meeting system. This skill allows users to monitor critical performance metrics, including transcription quality (using Ear-3 model), meeting coverage, action item extraction accuracy, and memory vault health. It is essential for implementing robust, enterprise-grade AI workflows and managing the operational status of advanced meeting AI applications.

A comprehensive guide for deploying and optimizing the Windsurf AI IDE across large, complex organizations (50+ developers). Covers critical enterprise topics including monorepo partitioning strategies, managing workspace performance degradation, central configuration distribution, credit budgeting models, and necessary network/IT infrastructure whitelisting for seamless large-scale adoption.

Defines strict guidelines for creating and maintaining Excel financial models, covering zero formula errors, industry color coding, number formatting, documented assumptions, and mandatory use of Excel formulas to ensure accuracy and auditability before recalculation.

This skill functions as a dedicated prompt engineer, transforming vague ideas or initial drafts into highly optimized, production-ready prompts. It adapts its methodology based on the target AI model (e.g., Claude, GPT, Midjourney), ensuring the best practices, structure, and constraints are applied for maximum output quality and token efficiency. Ideal for complex content generation, coding tasks, and creative visual prompts.

unslop is a powerful command-line interface (CLI) tool designed for post-processing text. It programmatically strips out common and identifiable patterns associated with AI-generated writing. Use it as a final, deterministic pass before publishing documentation, blog posts, or any content derived from large language models (LLMs), ensuring a more natural and human-like tone.

This skill analyzes and reports on the token usage, expenditure, and budget for AI models (like Claude Code) by querying a local SQLite database. It is essential for users who need detailed financial accountability, tracking costs by project, tool, or date, and managing operational budgets.

This skill analyzes and reports on the token usage, expenditure, and budget for AI models (like Claude Code) by querying a local SQLite database. It is essential for users who need detailed financial accountability, tracking costs by project, tool, or date, and managing operational budgets.