novel-review
ๅฐ่ฏด็ซ ่ๅฎกๆ ธ - ๅฝ้่ฆๆ กๅฏนใๅฎกๆ ธๅฐ่ฏด็ซ ่่ดจ้ๆถ่งฆๅใๅ ณ้ฎ่ฏ๏ผๅฎกๆ ธใๆ กๅฏนใๅฎก็จฟใๆฃๆฅใ่ดจ้่ฏไผฐใ
ๅฐ่ฏด็ซ ่ๅฎกๆ ธ - ๅฝ้่ฆๆ กๅฏนใๅฎกๆ ธๅฐ่ฏด็ซ ่่ดจ้ๆถ่งฆๅใๅ ณ้ฎ่ฏ๏ผๅฎกๆ ธใๆ กๅฏนใๅฎก็จฟใๆฃๆฅใ่ดจ้่ฏไผฐใ
Use this skill for requests related to web research; it provides a structured approach to conducting comprehensive web research
Search arXiv preprint repository for papers in physics, mathematics, computer science, quantitative biology, and related fields, Instructions for searching arXiv papers using Python script and shell tool. Read SKILL.md to learn the workflow.
Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.
12-agent academic paper writing pipeline. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, ๅฏซ่ซๆ, ๅญธ่ก่ซๆ, ๅผๅฐๆๅฏซ่ซๆ, ๅฏฉๆฅๆ่ฆ.
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 10-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.
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, ็ ็ฉถ, ๆทฑๅบฆ็ ็ฉถ, ๆ็ปๅ้กง, ๆ็ปๆข่จ, ็ณป็ตฑๆงๅ้กง, ๅพ่จญๅๆ, ไบๅฏฆๆฅๆ ธ, ๅผๅฐๆ็็ ็ฉถ, ๅนซๆ้ๆธ , ๅนซๆๆณๆณ, ๆไธ็ขบๅฎ่ฆ็ ็ฉถไป้บผ, ็ ็ฉถๆนๅ, ็ ็ฉถไธป้ก.
Search arXiv papers, download full text, follow citations, and run local semantic search.
Web search and content extraction via Brave Search API. Use for searching documentation, facts, or any web content. Lightweight, no browser required.
Analyze accumulated bug fix cases and propose updates to the self-testing checklist. Use periodically (weekly/monthly) to evolve quality checks based on real issues.
Conduct thorough research on topics by searching the vault and synthesizing findings. Use when the user asks to research a topic, dig into something across notes, or wants a synthesis of what the vault knows about a subject.
ALWAYS use before attempting any fix. Never jump to solutions - investigate root cause first. Use when encountering any technical issue, bug, test failure, or unexpected behavior.
Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.
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. Use this skill when writing documentation for MCC.
Semantic Similarity Index for disease research literature using PubMedBERT embeddings
Execute autonomous multi-step deep research on any topic. Use when the user asks for comprehensive research, literature reviews, competitive analysis, topic deep-dives, or wants to understand a complex subject from multiple angles. Triggers on "deep research", "research on", "investigate", "literature review", "comprehensive analysis", "what do we know about", "summarize research on".
Search PubMed and bioRxiv, summarise papers with LLM, build citation graphs, and generate literature review sections.
Generate daily or on-demand medical research briefs for any medical specialty. Searches latest research from top-tier journals, delivers concise summaries with 1-sentence takeaways, images when available, and direct links. Use when user asks for medical news, research updates, journal briefs, or specialty-specific medical updates for specialties like endocrinology, cardiology, oncology, neurology, etc.