Academic Deep Search
Use this skill for requests such as:
- - "What markers do studies on topic X usually measure?"
- "What do results sections in this field usually report?"
- "Show me a typical figure for this disease model or pathway."
- "What experimental methods are commonly used in this literature?"
The goal is not just to find papers. The goal is to read enough of the right papers to give the user a structured, directly useful answer.
Two Output Modes
Choose the mode that best matches the user request.
Body Mode
Use when the user asks about:
- - molecules or markers commonly measured
- methods commonly used
- what findings usually appear in Results sections
Organize the answer by experiment type or finding category, not by paper.
Figure Mode
Use when the user asks for:
- - a typical figure in a topic
- how findings are visually presented
- figure captions or representative panels
Organize the answer by figure, with source attribution and caption context.
Workflow
1. Clarify The Research Question
Identify:
- - the topic or disease area
- whether the user wants methods, markers, findings, or figures
- whether the user named a specific journal, database, or URL
- whether the topic is biomedical or from another field
If the topic is biomedical, translate the idea into standard English search terms and prefer controlled vocabulary when possible.
2. Respect Source Scope First
If the user specifies a source, that scope is binding.
Examples:
- - if the user says PubMed, do not mix in Google Scholar
- if the user names specific journals, search only those journals
- if the user gives a URL, read that source directly before searching elsewhere
Do not silently broaden the source list.
3. Build Search Terms Carefully
Use English search terms for database queries, even if the conversation is in Chinese.
For biomedical topics:
- - prefer MeSH or other standardized vocabulary when available
- generate a few close variants or synonyms
- keep journal names exact when filtering by journal
Detailed query construction tips are in references/query-guide.md.
4. Search For Candidate Papers
Prefer the best database for the topic:
- - biomedical: PubMed or PMC first
- quantitative or engineering topics: field-appropriate databases
- broad discovery: web search only when a better native source is unavailable
Aim to identify a small set of relevant papers with accessible full text. A few well-read papers are better than many shallow hits.
5. Verify Source Membership Before Citing
Before you cite a paper as belonging to a target journal or source, verify it.
Check:
- - journal field on the abstract page or database result
- exact source metadata in the database
- whether the paper truly matches the user-specified scope
Do not attribute a paper to a journal or database unless you confirmed it.
6. Read Full Text Strategically
Abstract-only answers are usually not enough.
Read:
- - Methods, Results, and Discussion for Body Mode
- figure captions plus the relevant Results text for Figure Mode
If full text is not available, say that clearly and lower confidence.
7. Select And Synthesize
Choose 2 to 5 papers that are:
- - relevant to the question
- compliant with the requested source scope
- diverse enough to avoid overgeneralizing from one paper
- rich enough in methods, results, or figures to support the answer
Then synthesize across papers instead of writing a paper-by-paper summary unless the user asked for that.
Output Rules
- - Answer directly in chat unless the user asks for a file.
- Use inline citations such as PMID, PMCID, DOI, or direct links.
- Be explicit about what was actually read.
- If evidence is limited, say so plainly.
Use references/query-guide.md for output templates.
Non-Negotiable Rules
- - User-specified source scope overrides your defaults.
- Do not answer methods or marker questions from abstracts alone if full text is available.
- Do not fabricate source membership or figure details.
- Prefer PubMed and PMC for biomedical literature.
- Translate search intent into English for querying, but answer in the user's language when appropriate.
If Results Are Sparse
When little is found:
- - broaden or narrow terms thoughtfully
- try synonyms or controlled vocabulary
- explain what was searched and why the yield was limited
- suggest the next best search strategy
学术深度搜索
使用此技能处理以下类型的请求:
- - 关于主题X的研究通常测量哪些标志物?
- 该领域的结果部分通常报告哪些内容?
- 给我展示这个疾病模型或通路的典型图表。
- 这类文献中常用的实验方法有哪些?
目标不仅是找到论文,而是通过深入阅读足够数量的正确论文,为用户提供结构化、可直接使用的答案。
两种输出模式
根据用户请求选择最匹配的模式。
正文模式
当用户询问以下内容时使用:
- - 常测量的分子或标志物
- 常用方法
- 结果部分通常出现的发现
按实验类型或发现类别组织答案,而非按论文组织。
图表模式
当用户询问以下内容时使用:
- - 某个主题的典型图表
- 发现如何以视觉方式呈现
- 图注或代表性图板
按图表组织答案,注明来源和图注上下文。
工作流程
1. 明确研究问题
确定:
- - 主题或疾病领域
- 用户需要的是方法、标志物、发现还是图表
- 用户是否指定了特定期刊、数据库或URL
- 主题是生物医学领域还是其他领域
如果是生物医学主题,将想法转化为标准英文搜索词,并尽可能优先使用受控词汇。
2. 优先遵循来源范围
如果用户指定了来源,该范围具有约束力。
例如:
- - 如果用户指定PubMed,不要混入Google Scholar
- 如果用户指定了特定期刊,仅搜索这些期刊
- 如果用户提供了URL,先直接阅读该来源,再搜索其他内容
不要擅自扩大来源列表。
3. 精心构建搜索词
即使对话语言为中文,数据库查询也使用英文搜索词。
对于生物医学主题:
- - 优先使用MeSH或其他标准化词汇(如可用)
- 生成几个相近变体或同义词
- 按期刊筛选时保持期刊名称准确
详细查询构建技巧见references/query-guide.md。
4. 搜索候选论文
优先选择最适合该主题的数据库:
- - 生物医学:首选PubMed或PMC
- 定量或工程主题:领域内合适的数据库
- 广泛发现:仅在无更合适的原生来源时使用网络搜索
目标是找到少量可获取全文的相关论文。精读几篇论文胜过浅尝辄止地浏览大量论文。
5. 引用前验证来源归属
在引用某篇论文属于目标期刊或来源之前,请进行验证。
检查:
- - 摘要页面或数据库结果中的期刊字段
- 数据库中确切的来源元数据
- 论文是否真正符合用户指定的范围
除非已确认,否则不要将论文归属于某个期刊或数据库。
6. 策略性阅读全文
仅基于摘要的答案通常不够。
阅读:
- - 正文模式:方法、结果和讨论部分
- 图表模式:图注及相关的结果部分文本
如果无法获取全文,请明确说明并降低可信度。
7. 选择与综合
选择2至5篇符合以下条件的论文:
- - 与问题相关
- 符合要求的来源范围
- 具有足够多样性,避免过度概括单篇论文
- 在方法、结果或图表方面足够丰富,以支持答案
然后跨论文进行综合,而非逐篇总结,除非用户明确要求。
输出规则
- - 除非用户要求文件,否则直接在对话中回答。
- 使用内联引用,如PMID、PMCID、DOI或直接链接。
- 明确说明实际阅读了哪些内容。
- 如果证据有限,请如实说明。
输出模板请参考references/query-guide.md。
不可协商的规则
- - 用户指定的来源范围优先于默认设置。
- 如果可获取全文,不得仅基于摘要回答方法或标志物问题。
- 不得虚构来源归属或图表细节。
- 生物医学文献优先使用PubMed和PMC。
- 查询时将搜索意图翻译为英文,但回答时酌情使用用户的语言。
结果稀疏时的处理
当找到的内容较少时:
- - 有策略地扩大或缩小搜索词
- 尝试同义词或受控词汇
- 解释搜索了什么以及结果有限的原因
- 建议下一步最佳搜索策略