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FORMAL VERIFICATION MODE is an advanced analytical framework focused on systematically validating correctness rather than simply generating answers. Each problem is processed through explicit inputs, clearly defined assumptions, step-by-step reasoning, and consistency checks. Outputs not only provide conclusions but also make the reasoning process transparent and traceable. Uncertainties are explicitly highlighted, and results are classified by confidence level.

A Claude Code skill (slash command) to open a PR after committing all outstanding changes and pushing them.

High-end Prompt Engineering & Prompt Refiner skill. Transforms raw or messy user requests into concise, token-efficient, high-performance master prompts for systems like GPT, Claude, and Gemini. Use when you want to optimize or redesign a prompt so it solves the problem reliably while minimizing tokens.

X (Twitter) data platform skill for AI coding agents. 122 REST API endpoints, 2 MCP tools, 23 extraction types, HMAC webhooks. Reads from $0.00015/call - 66x cheaper than the official X API. Works with Claude Code, Cursor, Codex, Copilot, Windsurf & 40+ agents.

This specification defines the operational parameters for a developer using Neovim, with a focus on the LazyVim distribution and cloud engineering workflows.

Transforms an Otter.ai transcript into a structured, visually appealing Notion page by organising content into clear sections, improving readability, and applying clean formatting with headings, bullet points, and callouts for a professional and engaging knowledge layout.

App Feature - Focused Readiness Audit

Creates, updates, and condenses the PROGRESS.md file to serve as the core working memory for the agent.

SOLVE THE QUESTION IN CPP, USING NAMESPACE STD, IN A SIMPLE BUT HIGHLY EFFICIENT WAY, AND PROVIDE IT WITH THIS RESTYLING: no comments, no space between operator and operand but proper margin and indentation, brackets open on the next line always and do not forget to rename variables as short as possible, possibly alphabets

Pick a feature from an existing AI like Gemini, Deep Research and create an instruction prompt for your agent based on size constraints. Features a 3+ time reason, write, read, role play, then refine loop.

Build an AI-powered Interview Preparation app as a single-page website using Streamlit (Python) or Next.js (JavaScript) in VS Code or Cursor. Integrate the OpenAI API, create a system prompt, and design prompts for interview preparation. The app can generate interview questions, practice exercises, analyze job descriptions, or simulate interviews. Experiment freely and use resources like ChatGPT or StackOverflow if needed.

An agent skill to work on a Linear issue. Can be used in parallel with worktrees.