Skill UI

Guides users through writing, reviewing, and editing documentation with consistent structure, tone, and accuracy; ideal when creating README files, updating docs folders, or refining markdown drafts per contribution standards.

A specialized skill designed for agents to proactively identify, analyze, and strategize high-impact contributions within trending Open Source repositories. It systematically performs repository discovery, extracts targeted issues (like 'help wanted' or 'good first issue'), and conducts deep feasibility analysis (including mergeability and complexity). Finally, it generates a structured 'Contribution Dossier' with actionable plans, significantly accelerating the process of becoming a top-tier OSS contributor.

A comprehensive, multi-agent protocol simulating a professional board meeting. It executes a structured 6-phase deliberation—from isolated C-suite contributions and critical analysis to final founder review and decision extraction. Use this when making complex, high-stakes strategic decisions requiring rigorous multi-perspective vetting and actionable documentation.

This skill transforms a refined research proposal or method idea into a detailed, structured, and claim-driven experiment roadmap. It helps users determine exactly which experiments to run, in what order, and what evidence is needed to support the core claims of a research paper, ensuring focus on novelty, simplicity, and genuine contribution.

This advanced skill systematically verifies the novelty of a proposed research method or technical idea against the global body of academic literature. It guides the user to extract core technical claims, performs multi-source searches across major academic databases (e.g., arXiv, Google Scholar, top conferences), and utilizes high-level LLM reasoning to generate a detailed, structured novelty assessment report. Ideal for researchers seeking to validate the unique contribution of their work.

Get a deep, multi-round, and adversarial critical review of your research work, ideas, or drafts. This skill simulates the perspective of a senior ML reviewer (e.g., NeurIPS/ICML level) using dedicated external backends (Codex or Manual). It is designed to find logical gaps, missing experiments, and narrative weaknesses, providing brutal honesty to elevate your academic contribution.

This tool systematically designs and plans ablation studies crucial for advanced research paper submissions. It simulates the role of a rigorous ML reviewer, guiding the process of isolating the specific contributions of each novel component, testing hyperparameter sensitivities, and addressing potential reviewer questions. The workflow ensures that every experiment has a clear hypothesis, maximizing the scientific impact of the research results.

Generates structured peer-review quality critiques of academic papers, covering summaries, methodology scrutiny, contribution evaluation, literature positioning, and recommendations across domains whenever a user requests reviews, analyses, or summaries of research publications.

Defines mandatory contribution guidance for repository work, insisting contributors locate workflow documentation, follow branch/commit/PR templates, and run required linters or tests before submitting changes, without executing forbidden scripts.

This skill provides comprehensive guidelines for contributing and managing commands within VS Code extensions. It covers crucial best practices, including naming conventions, defining visibility (e.g., Command Palette vs. Side Bar), and structuring commands for optimal user experience. Use this when adding, updating, or understanding the architectural requirements for extension commands.

Scans specified files or folders to infer existing syntax, writes a project coding standards or contribution doc using configurable templates, and optionally reports or fixes inconsistencies before saving to the first available standard filename.

This skill analyzes your entire codebase to ensure it is optimized for AI contributions and developer tooling. It automatically generates essential configuration files such as `AGENTS.md`, Copilot instructions, CI workflows, and customizable issue templates. It learns from your existing PR review patterns to tailor the setup precisely to your project's stack. Use it when you need to prepare a repository for advanced AI-assisted development.