Skill UI

Designs and optimizes AI agent execution by defining action spaces, tools, observation formats, recovery contracts, and context-budget strategies to boost completion rates and reliability.

Converts RDF context into belief-desire-intention structures so agents can track perceptions, deliberate plans, and emit explainable RDF, supporting BDI frameworks or LLMs needing structured cognition.

MolyKit is a Makepad-based toolkit for building cross-platform AI chat interfaces, handling SSE streaming, LLM integration, and reusable widgets like messages, prompts, avatars, and async task utilities.

Auri pairs Alexa hardware with Claude claude-opus-4-20250805 to deliver a Brazilian Portuguese conversational assistant that remembers context, reasons deeply, and integrates AWS services, making it ideal for product strategy sessions and voice-first demos.

Documentation for the Pipecat-powered Daily framework that guides agents through building production-ready real-time voice and multimodal AI pipelines, covering low-latency audio/video/text flows, transport choices, LLM/tool orchestration, and turn/context management.

Provides six structured AI engineering workflows—from prompt evaluation and context budgeting to RAG architecture, security audits, evaluation harnesses, and product sense coaching—ensuring repeatable, CI/CD-friendly decisions before deployment.

Deploys AI and NLP-powered detection to spot business email compromise by analyzing writing style, behavioral context, and intent, then integrates baselines, transformer models, and response workflows to surface impersonation attempts that rule-based filters miss.

Handles IMO/Putnam/USAMO/AIME style problems by generating refined proofs, then running a fresh-context adversarial verifier to catch flaws, finally producing honest confidence reports and verified PDFs when possible.

Structured workflow that has an AI agent capture failures, diagnose root causes, apply minimal recovery steps, and report introspection to avoid repeat loops or context drift.

This skill guides the generation of a complete, production-ready Model Context Protocol (MCP) server using C# and .NET. It covers advanced architectural patterns, including Host builder setup, proper dependency injection, structured logging, and implementing robust functional tools. Ideal for developers building sophisticated AI agents or backend services that require standardized communication and tool invocation capabilities.

This guide outlines the structure and content guidelines for an AGENTS.md file. This file serves as a comprehensive 'README for agents,' providing detailed, technical context and operational instructions (such as setup, development workflow, testing procedures, and code style) that enable advanced AI coding agents to interact with and understand a codebase effectively. It greatly complements traditional READMEs by focusing purely on machine-readable technical requirements.

FAF Expert configures IANA-registered .faf projects to deliver championship-grade AI-readiness, syncing context across Claude, Cursor, Gemini and more while managing MCP servers, scoring, and legacy modernization via a CLI workflow.