3. Data, Science & AI

Converts PDF, Word, images (with OCR), audio, and other formats to Markdown for AI/LLM processing and text analysis.

Predicts customer churn risk by analyzing behavioral and engagement data using machine learning models.

Crafts precise prompts to maximize AI model output quality and relevance for technical and creative applications.

Audits AI systems for safety risks, bias, and responsible deployment practices to ensure ethical and compliant AI operations.

CLI tool for searching clinical notes, listing cohorts, and exploring healthcare data databases in clinical research contexts.

Builds multi-agent AI workflows with orchestration, tool usage, and state management for coordinated AI systems.

Analyzes customer feedback to uncover patterns, derive actionable insights, and prioritize product or service improvements.

Performs advanced data analysis, pattern detection, and insight generation on both structured and unstructured datasets to drive data-driven decisions.

Constructs knowledge graphs to link concepts, articles, and solutions, enhancing information retrieval for support systems.

Extracts named entities (e.g., persons, organizations) from text with high accuracy and customizable parameters.

Builds end-to-end natural language processing pipelines for text analysis, enabling sentiment analysis and entity recognition tasks.

Builds and maintains structured knowledge bases optimized for AI retrieval and generation tasks.

Designs scalable vector similarity search systems for semantic content retrieval using AI-driven matching.

Orchestrates multiple AI agents and skills to execute complex, multi-step workflows efficiently.

Assists with computer vision tasks including image analysis, object detection, and visual AI model implementation.

Builds driver-based revenue projection models with scenario analysis and pricing optimization for business forecasting.

Automates iterative refinement of AI artifacts (prompts, agents) with parallel reviewers and anchor-based drift prevention to meet quality score targets.

Guides users in selecting optimal AI primitives from agentconfig.org based on workflow needs, skill level, and tooling preferences for effective AI configuration.

Generates interactive roundtable dialogue between tarot archetypes using embedded AI instruction engineering.

Crafts and refines prompts for LLMs, subagents, and task tools to improve model performance and task execution.

Automates refreshing token estimator and model pricing JSON files with real-time data from AI model providers.

Analyzes GitHub Copilot session logs to extract token usage, model information, and interaction data for debugging and tracking purposes.

Generates llms.txt and llms-full.txt files in the llmstxt.org standard for AI agent consumption, ensuring site content updates are reflected.

Toolkit for creating, editing, and analyzing spreadsheet data with formula support, formatting, and visualization capabilities.