Skill UI

Luna is an automated code reviewer focused on correctness, security, and reliability. She evaluates code against blueprints and checklists, identifying critical vulnerabilities like injection flaws, authentication bypasses, and race conditions. Luna acts as a quality gate, ensuring no unresolved high-risk issues proceed to QA or deployment. She excludes style preferences, focusing only on measurable risks to maintainability and safety.

Skill for triaging and working through Ouroboros GitHub issues and pull requests as a maintainer. Handles backlog cleanup, review, merge readiness, duplicate PRs, and issue disposition using live GitHub state and a defined review boundary.

Maintain a review-first engineering wiki with provenance, citation-aware queries, explicit capture and promotion, and deterministic checks. Helps teams capture durable lessons and verify knowledge before turning it into rules.

This skill acts as an ultra-advanced mathematician inspired by Terence Tao. It performs rigorous code and architecture analysis using deep mathematical theories such as information theory, graph theory, computational complexity, linear algebra, stochastic analysis, category theory, Bayesian probability, and formal logic. Ideal for complex algorithmic verification and architectural design review.

This skill functions as an optional agent companion for MDPR, a deterministic Markdown-to-presentation runtime. It helps review presentation workflows by providing semantic hints, visual evidence reports, and high-level layout intentions. Crucially, it keeps agent output evidence-based while letting MDPR maintain control over final slide geometry, rendering details, and layout coordinates.

MockHunter is an advanced skill designed to audit live web pages, providing a comprehensive reality check on visible data. It analyzes every element to determine its true source: whether it is REAL (from the database), MOCK (simulated data), LLM-generated, HARDCODED, BROKEN (broken endpoints), or UNKNOWN. Ideal for auditing AI-generated UIs or reviewing proof-of-concept MVPs before customer sign-off.

Expert skill for architecting, reviewing, and scaling software systems. Handles architecture, databases, microservices, and infrastructure design to create resilient backend solutions.

Expert in monorepo architecture, build systems, and dependency management at scale. Masters Nx, Turborepo, Bazel, and Lerna for efficient multi-project development. Use for scoped monorepo setup, build or dependency review, build optimization, or scaling development workflows across teams.

Simulate a structured peer-review process using multiple specialized agents to validate designs, surface hidden assumptions, and identify failure modes before implementation.

Design n8n AI agents, chains, classifiers, extractors, tool calling, memory, RAG, structured output, and human-review flows. Covers sub-node patterns, connection types, and best practices for production workflows.

S3-compatible object storage that branches alongside your Neon Postgres project, keeping files and database rows in sync across dev, preview, and production environments via copy-on-write buckets.

Delegate bounded coding tasks to the Oh My Pi (omp) CLI implementer, then review and land the resulting diff. Orchestrator writes the brief, relays it, and verifies output. Supports model selection, thinking levels, and read-only runs.