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Found 137 Skills
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 9-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.
Finalize an accepted ML or AI paper for camera-ready submission after reviews, rebuttal, and acceptance. Use this skill whenever the user has an accepted paper, camera-ready deadline, final revision, acceptance email, meta-review, rebuttal promises, author-response commitments, de-anonymization tasks, supplement updates, code links, acknowledgements, final LaTeX checks, or needs to ensure the accepted paper's claims, figures, references, and artifacts are consistent before final submission.
Build a retrospective or forward-looking work timeline from git commits, project docs, user notes, or chat records, then output a Markdown and/or HTML report with a Gantt chart or timeline visualization. Use when the user wants to review past work across one or more projects, explain time allocation to a mentor, summarize what was done in a period, or plan the next phase with a timeline.
Use the official MinerU (mineru.net) parsing API to convert a URL (HTML pages like WeChat articles, or direct PDF/Office/image links) into clean Markdown + structured outputs. Use when web_fetch/browser can’t access or extracts messy content, and you want higher-fidelity parsing (layout/table/formula/OCR).
Provides guidance for experiment tracking with SwanLab. Use when you need open-source run tracking, local or self-hosted dashboards, and lightweight media logging for ML workflows.
Design research plans and paper architectures. Given a research topic or idea, generate structured plans with methodology outlines, paper structure, dependency-ordered task lists, UML diagrams, and experiment designs. Use when starting a new research project or paper.
USE FOR web search, research, RAG, grounding, browse, find, lookups, fact-checking, documentation, agentic AI. All-in-one, optimized for AI agents. Pre-extracted, token-budgeted web content, deep research, news, images, videos, places, custom ranking
Use this skill for "write a literature review", "synthesize papers", "review the literature", "summarize research findings", "identify research trends", "gap analysis", "thematic review", "systematic review", "scoping review", "narrative review", "compare studies", "research synthesis", or when the user wants to synthesize multiple papers into a cohesive literature review.
Simulate target-conference reviewers for an ML/AI paper before submission. Use this skill whenever the user wants a reviewer-style critique, predicted scores, likely reject reasons, rebuttal risks, area-chair style meta-review, adversarial Reviewer 2 feedback, or venue-specific pre-review for conferences such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, or similar venues. This skill should dynamically inspect reviewer guidelines, example reviews, accepted papers, and project evidence when available.
Run a pre-submission citation and reference audit for LaTeX academic papers. Use this skill whenever the user wants to verify that BibTeX entries are correct, every citation key in TeX resolves, every figure/table/equation/section reference is valid, DOI/arXiv/OpenReview/proceedings metadata matches the cited work, citation claims are supported by the cited paper, or a paper is ready for submission with clean references.
Use when planning, running, auditing, or documenting systematic reviews, scoping reviews, PRISMA-style flows, screening decisions, inclusion criteria, exclusion criteria, or reproducible literature searches.
Use when preparing academic artifacts, reproducibility packages, artifact evaluation submissions, open science materials, code/data release, model cards, dataset cards, or replication bundles.