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Found 33 Skills
Use when the user asks for a literature review, academic deep dive, research report, state-of-the-art survey, topic scoping, comparative analysis of methods/papers, grant background, or any request that needs multi-source scholarly evidence with citations. Also trigger proactively when a user question clearly requires academic grounding (e.g. "what's known about X", "compare approach A vs B in the literature", "summarize the field of Y"). Runs an 8-phase (Phase 0..7), script-driven research workflow across 7 federated sources (OpenAlex, arXiv, Crossref, PubMed, DBLP, bioRxiv, Exa) with optional Semantic Scholar / Brave MCP enrichment, with deduplication, transparent ranking, dual-backend citation chasing (OpenAlex + Semantic Scholar), self-critique, and structured report output with verifiable citations.
Retrieve protein and nucleotide sequences from NCBI databases using E-utilities. Supports direct accession lookup, CDS translation, gene+organism search, locus lookup, PubMed-linked sequences, patent protein extraction, and organism+length fallback search. Use when you need to fetch biological sequences by accession, gene name, locus tag, PubMed ID, or patent number.
Search and retrieve clinical practice guidelines across 12+ authoritative sources including NICE, WHO, ADA, AHA/ACC, NCCN, SIGN, CPIC, CMA, CTFPHC, GIN, MAGICapp, PubMed, EuropePMC, TRIP, and OpenAlex. Covers disease management, cardiology, oncology, diabetes, pharmacogenomics, and more. Use when users ask about clinical guidelines, treatment recommendations, standard of care, evidence-based medicine, or drug-gene dosing recommendations.
Verify citations and references in scientific documents to detect hallucinated or invalid sources. Extracts DOIs, URLs, arXiv IDs, PubMed IDs, and ISBNs from Markdown, LaTeX, org-mode, and plain text, then validates them using API lookups and web fetches. Use this skill when: - Reviewing AI-generated content for citation accuracy - Validating references in papers, reports, or documentation - Checking if DOIs/URLs resolve to actual papers - Auditing a document for broken or fake citations
Comprehensive academic textbook chapter writing system for medical/scientific content. Use when the user wants to: (1) Write a full textbook chapter (5,000-15,000 words) on any medical/scientific topic, (2) Generate a detailed table of contents with section word counts, (3) Research topics via PubMed MCP and compile 20-30 references, (4) Write section-by-section with proper citations in Vancouver format, (5) Create publishable academic content with Eric Topol-inspired voice and authentic human prose, (6) Get approval at TOC stage before writing begins, (7) Export well-structured chapters for textbook publication.
Use when selecting, installing, configuring, smoke-testing, documenting, or troubleshooting MCP servers for academic search, arXiv, Semantic Scholar, OpenAlex, Crossref, PubMed, Zotero, Overleaf, Google Scholar, paper metadata, or scholarly source tooling.
Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.
Multi-source literature search, citation verification, MeSH search strategy, citation file management (.nbib/.ris/.bib conversion), and reference management (BibTeX, related articles, ID conversion) via MCP tools (PubMed, CrossRef, arXiv). Use when the user needs coordinated multi-step literature workflows beyond a single MCP call.
Solidify the workflow skill of "literature retrieval and scheduled push". It is used to create cron tasks for automatic retrieval + structured summary + multi-channel push (Feishu/WeCom/QQ/Telegram) for topics such as MDRGNB/HCC on a daily/weekly/monthly basis; supports field standardization (journal name, CAS Partition, SCI Partition), consistent content across multiple terminals, and long text segmentation to prevent loss. Trigger examples: "Help me push xx literature to xx at xx:xx", "Push xx topic literature to xx channel at xx:xx daily/weekly/monthly"