Skill UI

Simulates a highly structured, sequential peer-review process using multiple specialized AI agents (e.g., Skeptic, Constraint Guardian, User Advocate). This skill is designed to rigorously stress-test a design, surface hidden assumptions, identify potential failure modes, and enforce non-functional constraints before implementation. It transforms initial concepts into robust, validated specifications by simulating formal critique and achieving consensus via a mandatory Decision Log.

Structured manuscript and grant review guidance that walks reviewers through methodology, statistics, reporting compliance, and constructive feedback for rigorous scientific evaluation across disciplines.

This skill automates the research refinement process by entering an autonomous, multi-round review loop. It leverages any OpenAI-compatible LLM to score, critique, and guide necessary fixes until the work meets a high, expert-defined standard. It manages state persistence across rounds, simulating the rigorous process of professional peer review.

This skill implements an autonomous, multi-round research review loop, simulating the rigorous peer-review process of top-tier conferences. It iteratively reviews, identifies weaknesses, suggests fixes, and re-reviews a research document using the MiniMax API. The system manages state persistence across multiple rounds, ensuring continuous improvement until a 'ready' assessment is achieved or the maximum round limit is reached. Ideal for academic writing, thesis refinement, or comprehensive project documentation.

A specialized tool for finding peer-reviewed academic papers from major venues like IEEE, ACM, and Springer. Unlike preprint services (e.g., arXiv), this skill provides published literature with citation counts, detailed venue metadata, and a TLDR summary, ensuring access to verified research findings.

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.

A systematic framework designed for conducting rigorous peer reviews of scientific manuscripts and grant proposals. It provides a structured, checklist-based evaluation covering methodology rigor, statistical validity, reporting compliance (e.g., CONSORT, STROBE), and assesses all sections from abstract to results. Ideal for academic publishing, research quality assessment, and providing detailed, constructive feedback.

This skill provides a systematic framework for evaluating the rigor of scientific claims, research methodology, and evidence quality. It guides users through assessing experimental design validity, identifying various types of biases (e.g., selection, cognitive), and applying established grading frameworks like GRADE or Cochrane Risk of Bias. Ideal for systematic reviews, peer review, and critical analysis of scientific literature.

Drafts self-assessments, peer reviews, and upward feedback using WorkIQ evidence from emails, meetings, and contributions. It helps you write honest, impact-focused performance reviews in your own voice with STAR-based structure.

A powerful web toolkit powered by Exa, specifically optimized for scholarly and technical research. This skill handles advanced web searching (semantic lookups, current events) and precise URL content extraction (fetching articles, PDFs, and web pages). It excels in academic contexts, allowing users to bias results toward peer-reviewed papers and specific scholarly domains for high-quality, reliable information gathering.

A powerful 12-agent pipeline designed for academic writers, guiding users through the entire research publication lifecycle. It covers systematic literature review, structural outlining, full drafting, citation compliance, bilingual abstract generation, and simulating peer review. Features include Style Calibration and Writing Quality Checks to ensure high academic rigor and professional polish.

Simulates a rigorous international journal peer review process using an expert team of 5 reviewers (EIC, 3 Peers, Devil's Advocate). It assesses papers from multiple, non-overlapping perspectives—including methodology, deep domain expertise, and core argument challenges—to generate a structured editorial decision and revision roadmap. Supports modes for initial review, re-review of revisions, and methodology focus.