Skill UI

PydanticAI is a robust Python framework that integrates Pydantic's type-checking and validation capabilities into Large Language Models (LLMs). It allows developers to build production-ready AI agents that guarantee structured, validated outputs, moving beyond simple raw strings. Key features include supported tool calling, dependency injection for testability, and multi-model compatibility across major providers like OpenAI, Anthropic, and Gemini. Use this when reliability and correct data structure are paramount.

bdistill transforms AI interactions into a structured, queryable knowledge base. It extracts, structures, and quality-scores domain knowledge from both closed-source AI models (in-session) and local open-source models (via Ollama). Users can build comprehensive reference datasets, Q&A pairs, or generate structured training data for traditional machine learning, ensuring validated and exportable domain expertise.

JobGPT is a comprehensive automation platform for managing your entire career journey. It allows users to search for jobs using advanced filters (location, salary, remote, etc.), auto-apply to openings, generate tailored resumes optimized for specific roles, and track application progress across multiple job boards. Furthermore, it provides valuable salary intelligence, helps find target recruiters, and facilitates professional outreach, making the job hunt process highly efficient.

This skill manages comprehensive software development life cycle operations—including issue triage, PR reviews, version releases, bug fixing, and marketing content generation. It operates using a parallel "agent army" of dynamic agents (10-20 per task), requiring the user to adopt an Engineering Manager (EM) mindset. Key principles involve rigorous citation checking (anti-hallucination) and applying multiple roles (Product Owner, Open Source Contributor, Architect) simultaneously to ensure robust, safe, and user-centric outcomes across all platforms.

As a Cognitive Psychologist, this skill specializes in engineering email subject lines and notification copy that maximize open rates. It applies principles of behavioral psychology, such as the curiosity gap, self-referential processing, and pattern interruption, to create highly engaging and relevant communication triggers. Use this when you need to optimize messaging for specific audience psychographics, sequence stages, and desired emotional responses (e.g., urgency, relevance, curiosity), ensuring the subject line builds genuine interest rather than false hype.

Generates a standup-ready summary that combines today’s calendar meetings with open tasks via the GWS workflow command, offering JSON, table, YAML, or CSV output to keep updates concise and ready for reporting.

This skill provides explicit operations for managing durable OpenViking memories and resources. Users can `recall` past decisions or preferences, `read` linked `viking://` URIs to expand context, or `remember` information for explicit retention. It is essential for maintaining accurate context in advanced AI workflows.

A comprehensive guide for deploying, configuring, and maintaining the OpenViking server in production environments. It covers service configuration management, environment setup using `uv` for virtual environments, reliable startup procedures using `nohup`, graceful shutdown methods, and critical data cleanup workflows. This resource is essential for DevOps engineers and system administrators managing OpenViking services.

This guide teaches how to build well-structured and robust ASP.NET Minimal APIs. It covers best practices for API organization, defining clear DTOs with proper validation, handling strongly-typed parameters, and leveraging modern C# features. Crucially, it demonstrates how to generate comprehensive, standards-compliant OpenAPI/Swagger documentation using built-in .NET features, ensuring APIs are fully documented for seamless consumption.

This tool automates the entire process of creating a complete, production-ready application structure solely from an OpenAPI (Swagger) specification. It analyzes the spec to design the application architecture, generating all necessary layers including controllers, service logic, data models (DTOs), and repositories, adhering to best practices, framework conventions, and separation of concerns. The output includes unit tests, configuration files, and setup instructions, providing a robust, ready-to-use codebase.

This skill guides the integration of Arize AX tracing into existing applications, especially complex LLM applications. It follows a structured, two-phase, agent-assisted flow: first analyzing the codebase (read-only) to understand dependencies, and then implementing instrumentation. It supports multi-language environments (Python, TypeScript, Java, Go) and integrates deeply with OpenTelemetry and various LLM providers, ensuring comprehensive observability without altering core business logic.

Generates and edits draw.io (.drawio/.drawio.svg/.drawio.png) files via mxGraph XML, supporting templates, layout guidance, and the VS Code Draw.io extension so diagrams for flowcharts, architecture, UML, ER, sequences, and networks open without manual fixes.