Skill UI

Per-page Codex review and targeted python-pptx/Beamer fixes for academic talk slides. After /paper-slides when the deck looks mostly OK but needs a final pass, this skill aligns each slide's visual weight with a reference PDF, scales PPTX fonts to projector-readable sizes, removes italic style leaks, fixes text-frame overflow, and corrects per-slide layout drift. Ideal for final visual polish.

This expert playbook details advanced techniques for exploiting stack-based vulnerabilities, including classic buffer overflows, Return-Oriented Programming (ROP), ret2libc, and specialized gadgets like ret2csu and SROP. It provides comprehensive guidance on bypassing modern memory mitigations (NX, ASLR, PIE) to hijack program control flow and achieve reliable remote code execution in userland binaries.

This skill guides the design and optimization of production-grade multi-agent systems. It specializes in using LangGraph, LangChain, and DeepAgents to create structured, complex AI workflows. It covers state management, agent routing, memory integration, and tool calling, making it ideal for building robust, scalable agents like supervisors, planners, and coders.

This alias serves as a specialized Codex CLI interface for implementing the P7 protocol, mimicking the workflow of a P7 senior engineer. It enforces a highly structured development cycle: detailed planning, robust implementation, mandatory self-review (via three critical questions), and final, verifiable completion markers. Ideal for complex coding tasks requiring maximum rigor and accountability.

This CLI alias serves as the primary interface for the Codex /pua:pro protocol, designed for advanced code operations within the Claude Code environment. It manages complex workflows related to self-evolution, platform telemetry monitoring, key performance indicators (KPIs), and system configuration updates, ensuring robust and consistent protocol adherence.

A comprehensive guide for designing and implementing robust Infrastructure as Code (IaC) using Terraform or OpenTofu. Covers module hierarchy design, best practices for naming conventions, structuring multi-environment pipelines, advanced testing strategies (native tests, Terratest, static analysis), and integrating security scanning (trivy, checkov) into CI/CD workflows.

This skill provides a comprehensive framework for auditing and improving the efficiency of GitHub Codespaces environments. It helps users identify waste sources like oversized devcontainers, inefficient machine types, and poorly scoped prebuilds. By following a structured workflow, users can reduce monthly cloud spending, drastically cut startup times, and maintain optimal development throughput.

This guide provides a systematic, safe workflow for refactoring rapidly developed or AI-generated fullstack applications. It focuses on identifying and removing dead code, fixing broken imports, and consolidating repetitive logic while strictly maintaining existing API contracts, routes, and core functionality. Use this before launch to ensure a stable, maintainable production baseline, following a 'surgery, not demolition' philosophy.

This skill provides a comprehensive playbook for setting up and orchestrating multi-agent systems using the standalone Antigravity 2.0 Agent Manager alongside the Antigravity IDE. It guides developers on creating a dual-window workspace to coordinate specialized AI agents (e.g., front-end, back-end, QA) to work in parallel on a single codebase, significantly boosting development efficiency and managing concurrent code changes.

This skill analyzes your opencode prompt history to identify repeating multi-step workflows, recurring unmet needs, and candidates for new reusable skills. By scoring patterns based on frequency, complexity, and tool usage, it helps users save time and avoid repeating complex manual tasks.

This tool automates complex Git workflows to save time and reduce manual overhead. It intelligently detects and groups related code changes, automatically generates descriptive branch names (e.g., fix/auth-bug), and streamlines the entire cycle: staging, committing, pushing, and creating Pull Requests (PRs). Use it to maintain clean, consistent commit histories efficiently.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.