3. Data, Science & AI

Provides advanced prompt engineering techniques including chain-of-thought, few-shot, and system prompts to optimize AI model outputs.

Automates exploratory data analysis and visualization with minimal code, generating charts and detecting patterns for data insights.

Builds production-ready LLM applications using LangChain's chains, agents, memory, tools, and RAG pipelines.

Python library for creating, modifying, and analyzing Excel spreadsheets with formulas, charts, and large dataset handling.

Generates publication-quality tables in Python with advanced styling, conditional formatting, and export to HTML/images, inspired by R's gt package.

Generates automated data quality reports with variable analysis, missing value detection, and correlation analysis in HTML format.

Self-hosted platform for versioning, A/B testing, and metric-based evaluation of LLM prompts.

Compiles prompts into self-improving AI pipelines with signatures, modules, and optimizers for programmatic prompt engineering.

Provides AI-generated summaries and analysis of X/Twitter discussions using xAI Grok, focusing on trending topics and social sentiment without raw tweet data.

Optimizes website content for AI search engines and crawlers, analyzing factors like hedge density and discovery gaps to improve generative engine visibility.

Manages TikTok profiles for data scraping, enabling account switching, profile addition, and listing of saved profiles.

Transcribes all videos from a TikTok profile into text for content analysis and processing.

Transcribes TikTok video URLs into text using AI-driven speech recognition technology.

Provides structured problem-solving assistance using the Serena MCP framework for efficient issue resolution.

Researches a domain and generates a monorepo of 10 production-ready Lucid Agents using an autonomous agent factory.

Tracks custom events and conversions using Vercel Web Analytics for website interaction analysis and performance monitoring.

Persists AI chat conversations to Neon Postgres with full AI SDK message support, including tools and streaming, using UUID v7 for chronological ordering.

Installs and configures the Workflow Development Kit for building resumable, durable AI agent workflows with step-level persistence and orchestration.

Builds resumable multi-agent workflows with durable execution and automatic stream recovery upon client reconnection.

Generates descriptive chat titles from the first message using a fast LLM, running as a background step to avoid response delays.

Builds an AI chat application with database persistence, chat list management, and AI-generated conversation titles.

Analyzes large text documents using recursive language models and Nucleus DSL, enabling search, filter, and aggregation without loading entire content into context.

Builds a durable AI agent with control over streaming, provider configs, and tool loops, compatible with Workflow Development Kit.

Generates reproducible data science reports and presentations using Quarto, supporting code integration (R, Python, Stata) and output formats like HTML and Typst.