Skill UI

Lambda is a compact, machine-native communication protocol specifically designed for agent-to-agent (A2A) messaging. It functions as a shared, unambiguous vocabulary built from 'atoms' (2-character codes), completely bypassing the need for human natural language interpretation. It is ideal for orchestrators, task delegation, and logging structured coordination signals (like heartbeats or state changes) in multi-agent systems. Crucially, Lambda is intended only for machine communication, not for user-facing dialogue.

A comprehensive index of 46 production-grade test automation skills, covering E2E, unit, mobile, BDD, and cloud testing across 15+ languages. This skill equips AI coding assistants to act as senior QA architects, generating structured, real-world test code for major frameworks like Playwright, Selenium, Cypress, and Jest. It supports project setup, CI/CD integration, and cross-platform debugging.

Master the LangChain framework to build sophisticated LLM applications. Learn to implement agents, chains, memory management, and tool integration. This skill covers core concepts like ReAct agents, retrieval chains, and document processing pipelines. Ideal for creating autonomous AI agents and production-grade applications using Python.

Expert guidance for building production-grade stateful, multi-actor AI agents with LangGraph, covering graph construction, state management, cycles and branching, checkpoint persistence, human-in-the-loop patterns, and the ReAct agent workflow.

LEX is a structured truth engine designed to eliminate legal hallucinations by grounding AI agents in verified government references and legislation across 29+ jurisdictions (including US, EU, and CA). It provides deterministic context for comparing legal requirements, drafting compliant business, and employment documents, ensuring high jurisdictional accuracy.

Audit named agent instructions, tool definitions, and embedded prompts locally with LintLang 0.8.0. Reports finding codes, severities, and locations without editing files or calling a model.

Architecture and integration sketches for LLM applications, covering RAG retrieval, tool dispatch, agent loops, caching, privacy boundaries and verification requirements before production use.

Expert skill for building production-grade AI systems using LangChain 0.1+ and LangGraph. Covers agent architecture, RAG pipelines, memory systems, and deployment strategies. Ideal for developing sophisticated LLM applications with observability and scalability.

Conduct authorized security assessments for LLM applications and AI agents. Covers prompt injection, tool abuse, RAG exposure, memory poisoning, and system prompt extraction following OWASP LLM/ASI Top 10 guidelines. Includes red-teaming, vulnerability mapping, and compliance engineering for AI systems to ensure safety and robustness.

Loki Mode is a multi-agent autonomous startup system designed to execute workflows from PRD to production without human intervention. It integrates research-enhanced AI models including OpenAI SDK, DeepMind, Anthropic, and AWS Bedrock. This skill ensures zero human involvement in the deployment process while maintaining strict constraints on dependencies and response times.

Discover, find, compare, audit, repair, adapt, craft, run, debrief, and prepare repeatable AI-agent loops for publication. A comprehensive tool for managing bounded feedback loops in AI agent workflows.

Framework-agnostic long-term project memory for AI agents. Persists architecture decisions, conventions, and context as plain Markdown files in .lore/, enabling any agent to record, recall, audit, sync, and query project knowledge.