inno-deep-research
Comprehensive research assistant that synthesizes information from multiple sources with citations.
Comprehensive research assistant that synthesizes information from multiple sources with citations.
Search existing paper notes by title, author, keyword, or research domain
Daily paper recommendation workflow — search arXiv and Semantic Scholar, score and recommend papers
Deep analysis of a single paper — generate structured notes with figures, evaluation, and knowledge graph updates
This skill provides reference guidance for citation verification in academic writing.
Creates formal academic research papers following IEEE/ACM formatting standards with proper structure, citations, and scholarly writing style.
Structured manuscript/grant review with checklist-based evaluation.
Focused research analysis on a specific topic with sources
Search Semantic Scholar for academic papers on a given topic
Write competitive research proposals for NSF, NIH, DOE, and DARPA. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
Add field definitions to existing research outline.
Add items (research objects) to existing research outline.
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. 30c5c8d (Update humanizer plugin to upstream v2.2.0)
Searches X/Twitter for real-time perspectives, dev discussions, product feedback, breaking news, and expert opinions using the X API v2. Provides search with engagement sorting, user profiles, thread fetching, watchlists, and result caching. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", (2) user needs recent X discourse on a topic (library releases, API changes, product launches, industry events), (3) user wants to find what devs/experts/community thinks about a topic. NOT for: posting tweets or account management.
Creates formal academic research papers following IEEE/ACM formatting standards with proper structure, citations, and scholarly writing style. Use when the user asks to write a research paper, academic paper, or conference paper on any topic.
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
Requirements quality critique dimensions for peer review - confirmation bias detection, completeness validation, clarity checks, testability assessment, and priority validation
Critique dimensions and scoring for research document reviews
Source reputation tiers, cross-referencing methodology, bias detection, and citation format requirements
Use when researching products, finding academic papers, discovering competitors, reading webpage content, or getting cited answers grounded in real web sources. Use over generic search when semantic relevance matters.
Explore literature by fetching papers from OpenAlex with multi-dimensional filters (ISSN, concept, author, institution, keyword, etc.), building local embeddings, running BERTopic clustering, and multi-mode search (semantic/keyword/unified). Data is isolated in data/explore/<name>/. Use when the user wants to survey a journal, explore a research field, analyze an author's output, or do landscape analysis.
Verify citations in AI-generated or human-written text against the local knowledge base. Catches hallucinated references, wrong metadata, and missing papers. Use when the user wants to check if citations are real and accurate.