What problem does it solve?
This Skill solves the problem of turning vague literature requests into a real, checkable set of academic papers with canonical, traceable links instead of invented or unverifiable references.
Core Features & Use Cases
- Scope narrowing for vague topics: When the request is broad (e.g., “real literature addresses” or a general topic), it first clarifies the minimal missing constraints such as subtopic, language mix (Chinese/English), and time window.
- Discovery → verification workflow: It uses search-style discovery (e.g., Google Scholar-style) to surface candidates, then verifies each selected paper on publisher/DOI/CNKI/official pages before finalizing.
- Credibility screening and provenance clarity: It screens duplicates/low-quality/off-topic items, prioritizes top journals/conferences for foreign literature, flags preprints as provisional, and never fabricates titles/DOIs/links.
- Traceable output set: It returns a structured list (typically a table) including title, authors, venue, selection reasons, quality level, and the best canonical link (plus CNKI and DOI when available).
Quick Start
Ask the skill to “找真实文献综述用的可追溯链接,并筛选最近5年12-18篇中英文各半,输出表格包含标题、选择理由、真实地址、CNKI和DOI。”