tracking-discover
Use when the user wants crawl coverage, platform detection, dataLayer discovery, or a fresh artifact directory before grouping and schema work.
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Use when the user wants crawl coverage, platform detection, dataLayer discovery, or a fresh artifact directory before grouping and schema work.
Fetch and render web pages using the Servo browser engine — a single binary with JS execution, CSS layout, screenshots, and content extraction. Use when a URL returns empty or incomplete content with plain HTTP fetch, when you need a screenshot without GPU, or when you need to run JavaScript in a page context. No browser download required.
Domain-configurable Zotero-to-Obsidian literature curation and paper close-reading skill. Use when the user asks to 精读、文献精读、论文精读、生成精读笔记, analyze/read a paper, or process a Zotero item/collection/title/DOI/PDF into a structured Obsidian literature note. It extracts Zotero evidence, writes Chinese close-reading notes, maps original tags to a controlled taxonomy, initializes local config and empty taxonomy, handles review/survey papers with review_scope_tags, writes model and formula sections with LaTeX evidence discipline, and updates literature indexes for any research field.
Deep-read an arXiv paper and generate structured Deep Note reading notes. Default output: markdown deep note file (low token cost, git-friendly). Optional: HTML page from template. Trigger: 帮我读一下, DNL, 论文速读, paper notes, or an arXiv link.
Complete AI research assistant with 6 core capabilities: paper discovery, deep reading notes, reading list management, research taste learning, idea generation, and paper writing. Trigger words: 论文推荐, paper recommendation, arXiv, 读论文, paper notes, DNL, 推荐今日论文, 每日论文, 帮我读一下, paper scout, 论文速读, 帮我安装 ResearchClaw, research claws, researchclaw, 加入待读, 我的论文列表, reading list, 标记已读, 更新我的研究画像, 我的研究画像, research profile, 给我一些研究灵感, idea generator, 跨论文分析, 帮我写论文, paper writing, 论文大纲, 写引言, rebuttal.
Maintain and visualize the user research preference profile. Use when user says: 更新我的研究画像, 我的研究画像, research profile.
Fetch the Birkholz & Schlegel 2016 paper and its supporting information — the "standard method" (SM) that PyBerny's optimization algorithm follows — plus the papers it cites. Use when the user references the SM, asks about algorithm details/equations/convergence criteria, asks for test structures, asks about any of the SM's cited references (RFO, BFGS/SR1/PSB/Bofill, trust region, redundant internal coordinates, etc.), or asks anything that would be answered by reading [BirkholzTCA16] (cited in `doc/algorithm.rst`).
Retrieve clean markdown from URLs when web_fetch fails. Converts pages via Jina AI reader service with automatic retry. Use when web_fetch or curl returns 403, blocked, paywall, timeout, JavaScript-rendering errors, or empty content or user explicitly suggests using jina.
Analyze AI/ML technical content (papers, articles, blog posts) and extract actionable insights filtered through enterprise AI engineering lens. Use when user provides URL/document for AI/ML content analysis, asks to "review this paper", or mentions technical content in domains like RAG, embeddings, fine-tuning, prompt engineering, LLM deployment.