Skill UI

An interactive tool designed to discover, select, and assemble specialized teams of AI agents. It supports structured agent collections across different domains (e.g., Engineering, Marketing). Users select multiple roles for a specific task, and the skill launches them in parallel, synthesizing their independent findings into a unified report, including consensus and conflict analysis.

A comprehensive skill to extract and transcribe subtitles from any YouTube video URL. It utilizes a two-stage approach: first, attempting fast extraction via the yt-dlp CLI tool; failing that, it falls back to advanced browser automation using Chrome DevTools MCP to scrape the transcript panel content directly from the webpage DOM. The output is always a clean, timestamped plain text file.

Guides builders to verify task delivery by collecting required evidence such as CLI output, screenshots, or DOM snapshots, then submitting artifacts for review. Useful when a task must self-certify against a verify plan.

A comprehensive guide detailing the entire model lifecycle for RuView. It supports multiple advanced tracking methods including camera-free pose estimation (WiFlow), camera-supervised methods using MediaPipe, robust contrastive embeddings (RuVector), and domain generalization (MERIDIAN). Covers training, evaluation, and deployment across local GPU and cloud platforms.

Identifies high-leverage backlink prospects by analyzing domains that link to multiple competitors but not the brand. It ranks these prospects using an opinionated priority score combining authority (DR), link overlap, and topical relevance. This tool is essential for planning targeted link-building campaigns, qualifying digital PR leads, or conducting deep quarterly competitive gap audits.

This guide details how to position academic manuscripts within a specific geographic scholarly debate, rather than simply citing domain literature. It teaches authors to identify the "closest prior account," articulate a cross-cutting geographic stake, and engage with core geographic theories to enhance the impact of their findings for an advanced scholarly audience.

This guide helps researchers strategically decide if their AI project is a strong fit for the AAAI conference. It provides detailed criteria, including strong and weak signals, and routing logic to determine whether the work should be submitted to AAAI, or routed to specialized venues like NeurIPS, ICML, or domain-specific conferences (e.g., CVPR, KDD). Use it to refine your project's framing and maximize submission success.

Provides comprehensive guidelines for achieving scientific reproducibility in academic research, particularly for control systems, automation, and pattern recognition. It covers fixing environment dependencies, data handling, random seeds, and process pipelines, helping authors withstand rigorous peer review questioning and build verifiable research artifacts.

A comprehensive guide for authors submitting high-impact materials research. It details how to select expert referees (covering synthesis, device, and application domains) and provides actionable strategies to pre-empt common reviewer objections—such as claims of incremental advance, insufficient characterization, or weak benchmarking—thereby strengthening the manuscript's overall rigor and maximizing publication success.

This guide provides stringent methodological standards for establishing credible causal claims in empirical policy manuscripts. It covers advanced econometric techniques—including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity Design (RDD), and Randomized Controlled Trials (RCT)—required to move beyond mere correlation and prove that the observed effect is genuinely caused by the policy intervention.

A comprehensive guide for developing professional, self-contained, and APA 7th edition compliant tables and figures for academic manuscripts. It provides critical principles for preparing exhibits for masked review, ensuring accessibility, proper statistical reporting (e.g., SEs, CIs, random effects), and adherence to journal standards.

This guide helps researchers assess whether their education topic has broad significance for a general journal like AERJ, and how to define the dominant research lens (Policy, Teaching, Development, etc.). It provides a structured methodology for sharpening focus and improving academic framing.