Skill UI

Orchestrates PyTorch-native TorchTitan 4D parallelism (FSDP2, TP, PP, CP) for large-scale LLM pretraining, scaling from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing to boot Llama 3.1, DeepSeek V3, or custom models.

Framework for auditing and optimizing GEO content for each AI search platform, scoring Google AI Overviews, ChatGPT, Perplexity, Gemini, and Bing Copilot with tailored checklists and action steps.

This skill generates and ranks publishable research ideas based on a broad direction provided by the user. It systematically validates concepts through pilot experiments and model reviews, optimizing for GPU efficiency and novelty. Suitable for brainstorming sessions, academic exploration, and identifying workable research paths.

Orchestrate a complete idea discovery workflow that goes from a broad research direction to validated, pilot-tested ideas. Chains literature survey, idea generation, novelty checking, critical review, and research refinement into a single automated pipeline, producing a ranked idea report, a final proposal, and an experiment plan.

Orchestrates a robotics-specific literature survey, novel idea generation, novelty check, and critical review for embodied AI and robotics research. Helps turn a broad robotics direction (manipulation, locomotion, navigation, drones, humanoids) into benchmark-grounded, simulation-first pilot ideas. Use when you need robotics idea discovery or sim2real topic selection.

Get a multi-round adversarial critical review of your research ideas, papers, or experimental results from an external LLM reviewer backend (Codex or manual). Compiles a briefing, runs ultra-reasoning review rounds, and returns a verdict with logical gaps, missing experiments, and narrative weaknesses.

A comprehensive meta-skill template designed for developers to scaffold, structure, and define specialized Agent Skills for AI platforms like GitHub Copilot. It guides users through mandatory requirements, including folder naming conventions, YAML frontmatter best practices (name, description), and structuring the skill body with detailed workflows and documentation sections. Use this when building complex, specialized AI capabilities.

A comprehensive guide for developers to build advanced, declarative agents for Microsoft 365 Copilot. This skill details the integration process using a Model Context Protocol (MCP) server, allowing the agent to connect with external systems, select tools, and handle complex authentication (OAuth 2.0/SSO). You will learn to generate key JSON manifests required for deployment.

Deploy and govern MCP declarative agents within the Microsoft 365 admin center, managing their lifecycle, assignments, access controls, and compliance so Copilot delivers organizational capabilities securely.

Reads `.agent.md` or `.prompt.md` files, assesses task complexity, tooling, and requirements, then recommends the most cost-efficient GitHub Copilot model(s) (e.g., GPT-5, Claude Sonnet) with rationale for users across different subscription tiers and priorities.

Napkin gives Copilot CLI users a browser whiteboard to draw, sketch, and add sticky notes; Copilot reads snapshots and JSON data, then replies with analysis, suggestions, and next steps for business-oriented thinkers.

Generates concise TLDR-format summaries for GitHub Copilot customization files, MCP server docs, or related URLs, ensuring actionable examples and context-aware verbosity for inline or chat view sessions.